Disparate data aggregation for user interface customization

ABSTRACT

In some examples, there may be provided systems, devices, and methods for using data from disparate databases to determine characteristics of a set of users within an organizational unit and generate customized user interface elements for display within a user interface.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/545,998, filed Aug. 20, 2019, which claims the benefit of andpriority to U.S. Provisional Application No. 62/720,022, filed Aug. 20,2018, the entire contents of each is hereby incorporated by referencefor all purposes.

BACKGROUND

The amount of data generated each day continues to grow. In someenvironments, some of this data may be generated and stored by disparatesources be stored, while a majority of it may be evaluated and abandonedor ignored. Users and computing devices are beginning to rely more andon this data to make decisions. This may be especially true when thedata is introduced as part of an operational flow. However, the timerequired to sort through stored data can create inefficiencies and, insome examples, may prove difficult given the disparate approaches forstoring the data.

SUMMARY

This specification relates in general to aggregating data from disparatedata sources in a network environment and, but not by way of limitation,to aggregating the data and using the data for generation of customizeduser interfaces.

A system of one or more computers can be configured to performparticular operations or actions by virtue of having software, firmware,hardware, or a combination of them installed on the system that inoperation causes or cause the system to perform the actions. One or morecomputer programs can be configured to perform particular operations oractions by virtue of including instructions that, when executed by dataprocessing apparatus, cause the apparatus to perform the actions. Onegeneral aspect includes a computer-implemented method, including:retrieving, from a first database associated with a first computersystem, first data corresponding to reserved blocks of a plurality ofusers during a predefined period. The computer-implemented method alsoincludes retrieving, from a second database associated with a secondcomputer system, second data corresponding to a portion of thepredefined period, the second data including a plurality of activityactions obtained from at least one capture device. Thecomputer-implemented method also includes retrieving, from a thirddatabase, third data defining exchange conditions. Thecomputer-implemented method also includes determining first time foreach of the plurality of users based at least in part on the first datafrom the first database, the second data from the second database, andthe third data from the third database. The computer-implemented methodalso includes determining second time for each of the plurality of usersbased at least in part on the first data from the first database;categorizing each user of the plurality of users into one of a pluralityof categories by at least. The computer-implemented method also includesdetermining a third time based on the first time and the second time forthe respective user. The computer-implemented method also includesfiltering the third time with respect to a set of levels. Thecomputer-implemented method also includes assigning each user to one ofthe plurality of categories based at least in part on filtering thethird time. The computer-implemented method also includes generating afirst user interface element corresponding to a first category of theplurality of categories. The computer-implemented method also includesproviding a user interface for presentation at a user device thatincludes the first user interface element displayed in association witheach user categorized into the first category. Other embodiments of thisaspect include corresponding computer systems, apparatus, and computerprograms recorded on one or more computer storage devices, eachconfigured to perform the actions of the methods.

One general aspect includes a system, including: a memory configured tostore computer-executable instructions, and a processor configured toaccess the memory and execute the computer-executable instructions to atleast: retrieve, from a first database associated with a first computersystem, first data corresponding to reserved blocks of a plurality ofusers during a predefined period. The processor is also configured toretrieve, from a second database associated with a second computersystem, second data corresponding to a portion of the predefined period,the second data including a plurality of activity actions obtained fromat least one capture device. The processor is also configured toretrieve, from a third database, third data defining exchangeconditions. The processor is also configured to determine that a firstuser of the plurality of users accrues first extra time by arrivingbefore a first reserved block based on the first data from the firstdatabase, the second data from the second database, and the third datafrom the third database. The processor is also configured to determinethat the first user accrues second extra time by leaving after the firstreserved block based on the first data from the first database, thesecond data from the second database, and the third data from the thirddatabase. The processor is also configured to generate a first userinterface element corresponding to the first extra time. The processoris also configured to generate a second user interface elementcorresponding to the second extra time. The processor is also configuredto provide a user interface for presentation at a user device, the userinterface including the first user interface element and the second userinterface element displayed in association with the first user. Otherembodiments of this aspect include corresponding computer-implementedmethods, apparatus, and computer programs recorded on one or morecomputer storage devices, each configured to perform the actions of themethods.

Other objects, advantages, and novel features of the present disclosurewill become apparent from the following detailed description of thedisclosure when considered in conjunction with the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Various examples in accordance with the present disclosure will bedescribed with reference to the drawings, in which:

FIG. 1 is an example block diagram illustrating an interaction system inwhich techniques relating to aggregating data from disparate datasources for user interface customization may be implemented, accordingto at least one example;

FIG. 2 is an example block diagram illustrating an interaction system inwhich techniques relating to aggregating data from disparate datasources for user interface customization may be implemented, accordingto at least one example;

FIG. 3 is an example schematic model illustrating a networkcommunication model in which techniques relating to aggregating datafrom disparate data sources for user interface customization may beimplemented, according to at least one example;

FIG. 4 is an example schematic model illustrating an aspect of thenetwork communication model of FIG. 3 in more detail;

FIG. 5 is an example schematic model illustrating an aspect of thenetwork communication model of FIG. 3 in more detail;

FIG. 6 is an example schematic model illustrating an aspect of thenetwork communication model of FIG. 3 in more detail;

FIG. 7 is an example schematic model illustrating an aspect of thenetwork communication model of FIG. 3 in more detail;

FIG. 8 is an example schematic architecture illustrating an interactionsystem in which techniques relating to aggregating data from disparatedata sources for user interface customization may be implemented,according to at least one example;

FIG. 9 is an example schematic architecture illustrating a system inwhich techniques relating to aggregating data from disparate datasources for user interface customization may be implemented, accordingto at least one example;

FIG. 10 is an example diagram illustrating an aspect of a system inwhich techniques relating to aggregating data from disparate datasources for user interface customization may be implemented, accordingto at least one example;

FIG. 11 is an example diagram illustrating an aspect of a system inwhich techniques relating to aggregating data from disparate datasources for user interface customization may be implemented, accordingto at least one example;

FIG. 12 is an example diagram illustrating a user interface that hasbeen customized with data aggregated from disparate sources, accordingto at least one example;

FIG. 13 is an example diagram illustrating a user interface that hasbeen customized with data aggregated from disparate sources, accordingto at least one example;

FIG. 14 is an example diagram illustrating a user interface that hasbeen customized with data aggregated from disparate sources, accordingto at least one example;

FIG. 15 is an example diagram illustrating a user interface that hasbeen customized with data aggregated from disparate sources, accordingto at least one example;

FIG. 16 is an example diagram illustrating a user interface that hasbeen customized with data aggregated from disparate sources, accordingto at least one example;

FIG. 17 is an example flowchart illustrating a process for aggregatingdata from disparate data sources for user interface customization,according to at least one example; and

FIG. 18 is an example flowchart illustrating a process for aggregatingdata from disparate data sources for user interface customization,according to at least one example.

DETAILED DESCRIPTION

The ensuing description provides preferred exemplary example(s) only,and is not intended to limit the scope, applicability or configurationof the disclosure. Rather, the ensuing description of the preferredexemplary example(s) will provide those skilled in the art with anenabling description for implementing a preferred exemplary example. Itis understood that various changes may be made in the function andarrangement of elements without departing from the spirit and scope asset forth in the appended claims.

Referring first to FIG. 1, a block diagram of an example of aninteraction system 100 is illustrated. Generally, in interaction system100, data can be generated at one or more system components 102 and/oruser devices 104. Management engine 106 can manage the flow ofcommunications within interaction system. Transformative processingengine 108 can receive, intercept, track, integrate, process, and/orstore such data.

Data flowing in interaction system 100 can include a set ofcommunications. Each of one, some of all communications can include (forexample) an encoding type, authentication credential, indication of acontent size, identifier of a source device, identifier of a destinationdevice, identifier pertaining to content in the communication (e.g., anidentifier of an entity), a processing or reporting instruction, aprocedure specification, transmission time stamp, and/or sensormeasurement. Data may, or may not, selectively pertain to a particularentity and/or client. Data can, depending on the implementation, includeindividually identifiable information and/or de-identified informationas it pertains to an entity and/or client. Data may, but need not,include protected information.

For example, a system component 102 can include, for example, a sensorto detect a sensor measurement and can thereafter generate and transmita communication that reflects the sensor measurement. The communicationmay be transmitted at routine times and/or upon detecting a threshold(e.g., one or more) number of measurements or a measurement satisfying atransmission condition (e.g., exceeding a threshold value). In someinstances, the sensor measurement corresponds to one reflecting aproperty of an object or entity (e.g., person) near the sensor. Thecommunication may then include an identifier of the object or entity.The identifier can be determined, for example, based on detection of anearby electronic tag (e.g., RFID tag), a detected user input receivedat a user interface of component 102, and/or data in a correspondingcommunication received from a user device.

As another example, a user device 104 can be configured to detect inputreceived at an interface of the device. The input can include, forexample, an identifier of an object or entity, an instruction, acharacterization of an object or entity, an identification of anassessment to be performed, a specification of an aggregation or dataprocessing to be performed, and/or an identification of a destinationfor a data-analysis report. User device 104 can further be configured todetect input requesting particular data, to generate a requestcommunication (e.g., to be sent to transformative processing engine), toreceive the requested data and/or to present the received data.

The depicted engines, devices and/or components can communicate over oneor more networks. A network of one or more networks can include a wirednetwork (e.g., fiber, Ethernet, powerline ethernet, ethernet overcoaxial cable, digital signal line (DSL), or the like), wireless network(e.g., Zigbee™, Bluetooth™, WiFi™, IR, UWB, WiFi-Direct, BLE, cellular,Long-Term Evolution (LTE), WiMax™, or the like), local area network, theInternet and/or a combination thereof. It will be appreciated that,while one or more components 102 and one or more user devices 104 areillustrated as communicating via transformative processing engine 108and/or management engine 106, this specification is not so limited. Forexample, each of one or more components 102 may communicate with each ofone or more user devices 104 directly via other or the samecommunication networks.

A component 102 can be configured to detect, process and/or receivedata, such as environmental data, geophysical data, biometric data,chemical data (e.g., chemical composition or concentration analysisdata), and/or network data. The data can be based on data detected, forexample, via a sensor, received signal or user input. A user device 104can include a device configured to receive data from a user and/orpresent data to a user. It will be appreciated that, in some instances,a component 102 is also a user device 104 and vice-versa. For example, asingle device can be configured to detect sensor measurements, receiveuser input and present output.

A component 102 can be configured to generate a communication that is inone or more formats, some of which can be proprietary. For example, animaging machine (e.g., one of one or more components 102) manufacturedby company A, located within a first facility (e.g., facility 110), andbelonging to a first client, may save and transfer data in a firstformat. An imaging machine (e.g., one of one or more components 102)manufactured by company B, located within the first facility (e.g.,facility 110), and belonging to the first client, may save and transferdata in a second format. In some examples, data from certain componentsis transformed, translated, or otherwise adjusted to be recognizable bytransformative processing engine 108. Thus, continuing with the examplefrom above, when the imaging machines manufactured by companies A and Bare located within the first facility belonging to the first client,they may nevertheless save and transfer data in different formats. Insome examples, one or more components 102 communicate using a definedformat.

In some examples, each of one or more components 102 are each associatedwith one or more clients within a same or different interaction systems.For example, certain ones of one or more components 102 may beassociated with a first client, while other ones of one or morecomponents 102 may be associated with a second client. Additionally,each of one or more components 102 may be associated with a facility 110(e.g., client facility). Each facility 110 may correspond to a singlelocation and/or focus. Exemplary types of facilities include server farmfacilities, web-server facilities, data-storage facilities,telecommunication facilities, service facilities, and/or operationalfacilities. For example, a first facility may include a structure at afirst location at which one or more resources (e.g., computationalresources, equipment resources, laboratory resources, and/or humanresources) are provided. Each of the one or more resources may be of afirst type in a first set of types. A resource type can be identifiedbased on, for example, a characteristic of the resource (e.g., sensorinclusion) and/or a capability of providing each of one or moreservices. Thus, for example, resources at a first facility may be betterconfigured for handling a particular type of service requests comparedto those in another facility. As another example, different facilitiesmay include resources of similar or same types but may vary in terms of,for example, accessibility, location, etc.

Transmission of data from one or more components 102 to transformativeprocessing engine 108 may be triggered by a variety of different events.For example, the data may be transmitted periodically, upon detection ofan event (e.g., completion of an analysis or end of a procedure), upondetection of an event defined by a rule (e.g., a user-defined rule),upon receiving user input triggering the transmission, or upon receivinga data request from transformative processing engine 108. Eachtransmission can include, e.g., a single record pertaining to a singleentity, object, procedure, or analysis or multiple records pertaining tomultiple entities, objects, procedures, or analyses.

In some examples, at least some of one or more user devices 104 areassociated with facility 110. In some examples, at least some of one ormore user devices 104 need not be associated with facility 110 or anyother facility. Similar to one or more components 102, one or more userdevices 104 may be capable of receiving, generating, processing, and/ortransmitting data. Examples of one or more user devices 104 include, forexample, a computer, a mobile device, a smart phone, a laptop, anelectronic badge, a set-top box, a thin client device, a tablet, apager, and other similar user devices). One or more user devices 104 maybe configured to run one or more applications developed for interactingwith data collected by transformative processing engine 108. Forexample, those user devices of one or more user devices 104 that are notassociated with facility 110 may be configured to run one or morethird-party applications that may rely in part on the data gathered bytransformative processing engine 108.

Each of one or more components 102 and one or more user devices 104 maybe utilized by one or more users (not shown). Each of the one or moreusers may be associated with one or more clients. For example, one ofthe one or more users can be associated with a client as a result ofbeing employed by the client, physically located at a location of theclient, being an agent of the client, or receiving a service from theclient.

In some examples, one or more components 102 and one or more userdevices 104 may communicate with transformative processing engine 108and management engine 106 via different information formats, differentproprietary protocols, different encryption techniques, differentlanguages, different machine languages, and the like. As will bediscussed with reference to FIG. 2, transformative processing engine 108is configured to receive these many different communications from one ormore components 102, and in some examples from one or more user devices104, in their native formats and transform them into any of one or moreformats. The received and/or transformed communications can betransmitted to one or more other devices (e.g., management engine 106,an entity device, and/or a user device) and/or locally or remotelystored. In some examples, transformative processing engine 108 receivesdata in a particular format (e.g., the HL7 format) or conforming to anyother suitable format and/or is configured to transform received data toconform to the particular format.

One or more components 102 of facility 110 can include and/or has accessto a local or remote memory for storing generated data. In someexamples, the data is stored by one or more servers local to facility110. The record service can be granted access to the data generatedand/or transmitted by one or more components 102. In some examples, therecord service includes a server or a plurality of servers arranged in acluster or the like. These server(s) of the record service can processand/or store data generated by one or more components 102. For example,one or more records can be generated for each entity (e.g., each recordcorresponding to a different entity or being shared across entities).Upon receiving a communication with data from a component (or facility),the record service can identify a corresponding record and update therecord to include the data (or processed version thereof). In someexamples, the record service provides data to transformative processingengine 108.

Irrespective of the type of facility, facility 110 may update data,maintain data, and communicate data to transformative processing engine108. At least some of the data may be stored local to facility 110.

A user interacting with a user device 104 can include, for example, aclient customer, client agent and/or a third party. A user may interactwith user device 104 and/or component 102 so as to, for example,facilitate or initiate data collection (e.g., by a component 102),provide data, initiate transmission of a data request, access dataand/or initiate transmission of a data-processing or data-storageinstruction. In some instances, one or more user devices 104 may operateaccording to a private and/or proprietary network or protocols. In otherexamples, one or more user devices 104 may operate on public networks.In any case, however, transformative processing engine 108 can haveaccess to the one or more components and can communicate with them via apublic, private, and/or proprietary network or protocols. The use of oneor more private and/or proprietary protocols can promote secure transferof data.

Referring next to FIG. 2, a block diagram of an example of aninteraction system 200 is shown. Interaction system 200 includes atransformative processing engine 202. Transformative processing engine202 is an example of transformative processing engine 108 discussed withreference to FIG. 1. Interaction system 200 also includes one or moregeneration components 204. In particular, one or more generationcomponents 204 include an equipment component 206, a lab systemscomponent 208, a temporal component 210, and other generation component212. One or more generation components 204 are examples of one or morecomponents 102 discussed with reference to FIG. 1. In some examples, thedata may pass to the transformative processing engine 202 via aninformation exchange service bus 236 (e.g., an enterprise service bus).In some examples, only a portion of the is passed via the informationexchange service bus 236, while other portions are passed directly tothe transformative processing engine 202 without first passing over theinformation exchange service bus 236.

Generally, one or more generation components 204 includes any suitabledevice or system capable of generating data in the context of aninteraction system. For example, the other generation component 212 mayinclude a sensor on a door, and equipment component 206 may include asophisticated computer-controlled laser device. In either case, eachgeneration component generates some type of data. For example, the dataprovided by the sensor may be used to address security concerns orassessing heating, ventilating, and air conditioning (HVAC) costs for aninstitution. The data provided by the laser device may have beenprovided while engaged in a procedure and may then be used by otherentities in the future to decide how to use the device.

As discussed in further detail herein, data generated by one or moregeneration components 204 can be of a variety of formats, some of whichmay be proprietary. For example, a single component can generate data inmultiple formats, different components can generate data in differentformats, and/or different component types can result in generation ofdata in different formats. In some instances, formatting of a data candepend on a service having been provided, a user initiating datageneration, a destination to receive the data, a location at which aservice was provided, etc. In some examples, a typical interactionsystem includes thousands of generation components producing data inhundreds of formats. In order to harness the power that comes from sucha large amount of data to make informed decisions, it is desirable thatall, or at least a large portion of the data, is shared. Use oftransformative processing engine 202 in accordance with techniquesdescribed herein may achieve this design—making large amounts of data,in many different originating formats available to various types ofusers, via one or more interfaces. At least a portion of the datagenerated by the generation components 204 may be provided to thetransformative processing engine 202. In some examples, each generationcomponent 204 includes an agent that executes on the generationcomponents 204 and determines which data to send to the transformativeprocessing engine 202 and other engines described herein. In someexamples, the generation components 204 provide data to thetransformative processing engine 202 via a messaging bus (e.g., aninformation exchange service bus 236). The messaging bus, which may beincluded in the transformative processing engine 202 or separate, isable to see data that moves throughout the interaction system 200. Theinformation exchange service bus 236 also includes a subscriptionregistry that can be used to manage subscriptions to the informationexchange service bus 236 for certain data (e.g., data having certaincharacteristics). The information exchange service bus 236 may sendand/or direct data to certain other entities when appropriate asindicated by subscription records in the registry.

While one or more generation components 204 are illustrated adjacent toeach other, it is understood that each may be located within onefacility or that the components may be spread out among many facilities.In addition, in some examples, one or more generation components 204belong to different clients.

Turning now to equipment component 206, this component includes anymachine, contrivance, implant, or other similar related article, that isintended to aid in reaching a particular objective. In some instances,equipment component 206 includes one or more sensors to detectenvironmental or other stimuli. Equipment component 206 can include, forexample, equipment to monitor a stimulus, detect stimulus changes,detect stimulus-indicative values, and so on. Exemplary equipmentcomponents 206 include an imaging device, a device that detects andcharacterizes electrical signals, a device that detects pressure, and/ora device that detects concentration of one or more particular elements,compounds and/or gases.

As illustrated, equipment component 206 includes transformative adaptor216. In some examples, transformative adaptor 216 is a device thattransforms, translates, converts, or otherwise adjusts output data fromequipment component 206. For example, an equipment component 206 can bea scanner that outputs its results in format A, but the majority ofother scanners in the interaction system output their results in formatB. Transformative adaptor 216 may be implemented to convert or otherwiseadjust the results in format A to conform closer to format B. Forexample, the conversion from format A to format B may be performed usinga conversion rule, which may be user-define or learned. Transformativeprocessing engine 202 may perform similar tasks as it relates to alldata generated within interaction system 200. In this manner,transformative adaptor 216 can perform an initial step in the process oftransformation, translation, conversion, or adjustment of the output ofequipment component 206. In some examples, transformative adaptor 216 isimplemented in hardware, software, or any suitable combination of both.In some examples, other transformative adaptors (not shown) may beimplemented within others of one or more generation components 204. Insome examples, equipment component 206 may not include transformativeadaptor 216.

Lab systems component 208 includes any suitable laboratory equipment orsystem that is intended to analyze material, such as biologicalmaterial. This includes, for example, laboratory equipment that analyzesbiological samples; electric microscopes; ultracentrifuges; datacollection devices, including Kymographs, sensors connected to acomputer to collect data; monitoring devices; computers used to reportresults of lab tests, and other similar laboratory equipment. Each ofthe above-listed components generates data that is provided (directly orindirectly) to transformative processing engine 202.

Temporal component 210 may include any suitable computing devices usedwith respect to interaction system 200. For example, temporal component210 can be configured to allocate a resource to a particular entityduring a particular temporal window. Temporal component 210 can monitora schedule for the resource and can identify one or more availabletemporal windows that may be secured by a particular entity. Uponreceiving an indication, temporal component 210 may update a schedule ofa resource to reflect that a particular temporal window is to beallocated for service of a particular entity.

Each of one or more generation components 204 and the user device 228may include individual and/or shared storage systems, one or moreprocessors, a user interface, a network connectivity device, and one ormore ports. The storage system include memory that may be implemented,e.g., using magnetic storage media, flash memory, other semiconductormemory (e.g., DRAM, SRAM), or any other non-transitory storage medium,or a combination of media, and can include volatile and/or non-volatilemedia. The storage systems may also be configured to storecomputer-executable code or instructions for interacting with the userinterface and/or for one or more applications programs, such as anapplication program for collecting data generated by the particulargeneration component.

The one or more processors may be configured to access the operatingsystem and application programs stored within the storage systems, andmay also be configured to execute such program code. The one or moreprocessors can be implemented as one or more integrated circuits, e.g.,one or more single-core or multi-core microprocessors ormicrocontrollers, examples of which are known in the art. In operation,the one or more processors can control the operation of the particularcomponent. The one or more processors may access and execute the programcode and at any given time.

The user interface can include any combination of input and outputdevices. In some instances, a user can operate input devices of the userinterface to invoke the functionality of the particular component oruser device. For example, the user interface may enable the user toview, hear, and/or otherwise experience output from component or userdevice via the output devices of the user interface. Examples of outputdevices include a display, speakers, and the like.

The network connectivity device may enable the component or user deviceto communicate with transformative processing engine 202 and othercomponents or other user devices via one or more networks. The one ormore networks may include any suitable combination of cable, cellular,radio, digital subscriber line, or any other suitable network, which maybe wired and/or wireless. In some examples, the network connectivitydevice may enable the component or the user device to communicatewirelessly with various other components and/or transformativeprocessing engine 202. For example, the components may include circuitryto enable data communication over a wireless medium, e.g., usingnear-field communication (NFC), Bluetooth Low Energy, Bluetooth® (afamily of standards promulgated by Bluetooth SIG, Inc.), Zigbee, Wi-Fi(IEEE 802.11 family standards), or other protocols for wireless datacommunication.

The one or more ports may enable the component or the user device toreceive data from one or more sensors. The sensors may be any suitabletype of sensor to capture data. Such captured data may be shared withtransformative processing engine 202 in accordance with techniquesdescribed herein. In some examples, the sensors may also be configuredto detect the location and other details about the component or the userdevice. In some examples, the component and the user device may includeglobal positioning chips that are configured to determine a geolocation.

Transformative processing engine 202 includes an aggregation engine 218,an interoperability engine 220, an access management engine 222, aninterface engine 224, and a data store 226. Generally aggregation engine218 is configured to collect data from multiple communications. The datamay be from one or multiple generation components 204 and/or may be ofsame or different formats. Aggregation engine 218 may be configured toperform one or more operations on the collected data. For example,aggregation engine 218 may tag data, log data, perform protocolconversion, and may support one-to-many communications. The collectionmay be asynchronous. In some examples, the data has been saved locallyin connection with one or more generation components 204 in manydifferent formats having many different data structures.

Aggregation engine 218 can identify data to be aggregated based on, forexample, intra-communication data, a current time, a source generationcomponent, and/or one or more aggregation rules. For example, anaggregation rule may specify that data is to be aggregated across allcommunications that include content with a same entity identifier. Anaggregation may be dynamic. For example, aggregated data may reflectthat from within a most recent 12-hour period. Thus, an aggregation maybe updated in time to exclude older data from the aggregation and toinclude newer data.

Aggregation engine 218 can be configured to provide data from one ormore communications to interoperability engine 220. Interoperabilityengine 220 can be configured to perform one or more operations on thereceived data and store it in data store 226. For example,interoperability engine 220 may perform semantic tagging and indexing ofdata. This may include extracting field values from data, categorizingdata (e.g., by type of data, characteristic of an entity, location offacility, characteristic of facility, and the like), anonymizing orpartially-anonymizing data, and the like. Interoperability engine 220may also include a high availability cache, an alerts engine, and arules engine. In some examples, interoperability engine 220 operatessynchronously.

From interoperability engine 220, data flows to data store 226. Datastore 226 (and any other data store discussed herein) may include one ormore data stores, which may be distributed throughout two or moredifferent locations (e.g., present on different devices, which caninclude devices of different entities and/or a cloud server). In someexamples, data store 226 includes a general data store 230, anoperational data store 232, and an entity-based data store 234. Withineach of the data stores 230, 232, and 234 is stored data. Depending onthe structure of the particular data store, certain data stores mayinclude rules for reading and writing. The data stores 230, 232, and 234may include records, tables, arrays, and the like, which may berelational or non-relational. Depending on the data store, records forindividual entities, business and analytics information, output datafrom one or more generation components 204, and the like may beretained. The data within the data stores 230, 232, and 234 includeelements or tags such that a particular data (e.g., for a single entity,protocol, etc.) can be retrieved.

Access management engine 222 is configured to manage access to featuresof transformative processing engine 202, including access to the dataretained in data store 226. For example, access management engine 222may verify that a user device such as user device 228 is authorized toaccess data store 226. To verify the user device 228, access managementengine 222 may require that a user of the user device 228 input ausername and password, have a profile associated with the interactionsystem, and the like. Access management engine 222 may also verify thatthe user device 228 has an IP address or geographical location thatcorresponds to an authorized list, that the user device 228 includes aplug-in for properly accessing the data store 226, that the user device228 is running certain applications required to access the data store226, and the like.

Interface engine 224 is configured to retrieve the data from data store226 and provide one or more interfaces for interacting with elements oftransformative processing engine 202. For example, interface engine 224includes an interface by which an application running on user device 228can access portions of data within data store 226.

As described herein, an information exchange engine 238 shares a networkconnection with the information exchange service bus 236. Theinformation exchange engine 238 is configured to monitor data (e.g.,messages) that is passed over the information exchange service bus 236and, from the monitored data, select certain portions to provide to oneor more authorized user devices. The information exchange engine 238 isalso configured to route inbound messages and route outbound messages,as described herein. The information exchange engine 238 is alsoconfigured to generate customized messages based on dependent user data.

Turning next to FIG. 3, an architecture stack 300 is shown. In someexamples, techniques relating management of data are implemented inaccordance with architecture stack 300. And while architecture stack 300is illustrated as having a particular structure, it is understood thatother structures, including those with more or less layers thanillustrated, is within the scope of this specification. In someexamples, architecture stack 300 is implemented across an interactionsystem having a plurality of systems belonging to the same client orspread across different clients. Thus, architecture stack 300 can beused to integrate different systems of different organizations,entities, and the like and to provide a fluid sharing of informationamong elements within the interaction system and without the interactionsystem. In some instances, a multi-layer part of architecture stack 300is implemented at a single system or device within an interactionsystem.

The different layers of architecture stack 300 will be describedgenerally with reference to FIG. 3 and in detail with reference tosubsequent figures. Architecture stack 300 includes a receiving layer302 as the bottom-most layer. Receiving layer 302 includes receivingdata from elements that share data with other elements within anaggregation layer 304. For example, as detailed herein, receiving layer302 can include receiving data from generation components that generatedata. As such, receiving layer 302 is where data that has been createdis received. In some examples, the data within receiving layer 302 maybe in its raw formats. The output may then be transmitted to aggregationlayer 304. In some examples, components of receiving layer 302 may havecomplimentary layers to facilitate data transfer. For example, thecomponents may include a data generation and/or a data transmissionlayer for providing data to receiving layer 302.

Elements of aggregation layer 304 aggregate the data generated by theelements of receiving layer 302. For example, the elements ofaggregation layer 304 may include aggregation engines that collect datafrom generation components located within receiving layer 302. Suchaggregation may be performed periodically, in response to a userrequest, according to a schedule, or in any other suitable manner. Insome examples, data of aggregation layer 304 may be aggregated accordingto input and/or rules and may aggregate across records pertaining to,e.g., a facility, entity, time period, characteristic (e.g., demographiccharacteristic or condition), outcome, and any other suitable inputand/or rules. The aggregation may include compiling the data, generatinga distribution, generating a statistic pertaining to the data (e.g.,average, median, extremum, or variance), converting the data,transforming the data to different formats, and the like.

Next, architecture stack 300 includes an active unified data layer 308.Elements of active unified data layer 308 receive data from the elementsof the other layers and store such data in a unified manner. In someexamples, this may include storing the data in a manner that allows forlater searching and retrieval using a defined set of method calls,techniques, and or procedures. For example, the data may be stored suchthat a different application can access the data in a standard orunified manner. Thus, elements of active unified data layer 308 mayreceive information collected or generated within aggregation layer 304and make certain adjustments to the data (e.g., translations, tagging,indexing, creation of rules for accessing the data, conversion offormatting of the data, generation of compressed versions, and the like)prior to retaining the data within one or more data stores accessiblewithin active unified data layer 308.

Architecture stack 300 also includes an access management layer 310,which can include an audit/compliance layer 312 and/or an agency layer314. Access management layer 310 includes elements to manage access tothe data. For example, access management layer 310 may include elementsto verify user login credentials, IP addresses associated with a userdevice, and the like prior to granting the user access to data storedwithin active unified data layer 308.

Audit/compliance layer 312 includes elements to audit other elements ofarchitecture stack 300 and ensure compliance with operating procedures.For example, this may include tracking and monitoring the other elementsof access management layer 310.

Agency layer 314 includes an access location (e.g., a virtual privatenetwork, a data feed, or the like) for elements of agencies that areinterested in the operations of the interaction system in whicharchitecture stack 300 is implemented. For example, agency layer 314 mayallow a governmental entity access to some elements within architecturestack 300. This may be achieved by providing the governmental entity adirect conduit (perhaps by a virtual private network) to the elements ofaccess management layer 310 and the data within active unified datalayer 308. Audit/compliance layer 312 and agency layer 314 aresub-layers of access management layer 310.

Architecture stack 300 also includes interface layer 316. Interfacelayer 316 provides interfaces for users to interact with the otherelements of architecture stack 300. For example, clients, entities,administrators, and others belonging to the interaction system mayutilize one or more user devices (interacting within application/devicelayer 320) to access the data stored within active unified data layer308. In some examples, the users may be unrelated to the interactionsystem (e.g., ordinary users, research universities, for profit andnon-profit research organizations, organizations, and the like) and mayuse applications (not shown) to access the elements within architecturestack 300 via one or more interfaces (e.g., to access data stored withinactive unified data layer 308). Such applications may have beendeveloped by the interaction system or by third-parties.

Finally, architecture stack 300 includes application/device layer 320.Application/device layer 320 includes user devices and applications forinteracting with the other elements of architecture stack 300 via theelements of interface layer 316. For example, the applications may beweb-based applications, entity portals, mobile applications, widgets,and the like for accessing the data. These applications may run on oneor more user devices. The user devices may be any suitable user deviceas detailed herein.

Turning next to FIG. 4, a diagram 400 is shown that depicts a portion ofarchitecture stack 300 according to at least one example. In particular,the diagram 400 includes receiving layer 302, aggregation layer 304,aggregation layer 306, and a portion of active unified data layer 308.Receiving layer 302 receives data from one or more components 410-418.Components 410-418 are examples of one or more generation components204. Components 410-418 may be spread across multiple facilities withina single or multiple clients. In some examples, components 410-418 mayinclude complimentary layers to facilitate data transmission. Forexample, components 410-418 may include a transmission layer, generationlayer, and/or a receiving layer to communicate data at receiving layer302 and, in some examples, receive data from receiving layer 302.

In some instances, two or more of components 410-418 generate dataaccording to different formats. The data can then be transformed,translated, or otherwise adjusted before an aggregation engine 420(e.g., aggregation engine 218) or a third-party aggregation engine 422(e.g., aggregation engine 218) collects the data. In some examples, theadjustment takes place within receiving layer 302. Thus, an adaptor 424is associated with component 412 located in receiving layer 302. Adaptor424 is an example of transformative adaptor 216. Adaptor 424 isimplemented, as appropriate, in hardware, software, or any suitablecombination of both. For example, transformative adaptor 216 may be abolt-on adaptor that adjusts data as such data leaves component 412.

Other adaptors, such as adaptor 426 and adaptor 428, are implementedwithin aggregation layer 304. These adaptors can function in a similarmanner as adaptor 424. In some examples, the data provided by component414 is transmitted through adaptor 426 prior to being directed toaggregation engine 420. The data provided by component 416 istransmitted through aggregation layer 304 and/or enters aggregationengine 420 without having first traveled through an adaptor. The dataprovided by component 418 is transmitted through aggregation layer 304and through adaptor 428. In some examples, component 418 provides forstreaming of data. The data provided by component 410 is transmitteddirectly to third-party aggregation engine 422.

Aggregation engine 420 and third-party aggregation engine 422 functionin a similar manner. In some examples, third-party aggregation engine422 is operated by a different entity than the entity that operatesaggregation engine 420 and may belong to different clients or adifferent interaction system. This may be because the data collected bythird-party aggregation engine 422 differs in some way from the datacollected by aggregation engine 420. In any event, aggregation engine420 is configured to perform integration of data, including genericintegration. For example, aggregation engine 420 performs one or moreoperations on data including tagging, logging, and protocol conversion.Aggregation engine 420 also supports one-to-many communications of data.In some examples, data flows between aggregation engine 420, thethird-party aggregation engine 422, and some of components 410-418 andelements of active unified data layer 308.

The diagram 400 also includes the information exchange service bus 236and the information exchange engine 238. As introduced herein, messagespassing through the aggregation layer 304 can pass over the informationexchange service bus 236. In this manner, the information exchangeengine 238 can access the messages, route the messages, and/or customizethe messages.

Referring next to FIG. 5, a diagram 500 is shown that depicts a portionof architecture stack 300 according to at least one example. Inparticular, diagram 500 includes active unified data layer 308 and aportion of access management layer 310. Active unified data layer 308,as illustrated in diagram 500, includes an interoperability engine 502(e.g., interoperability engine 220), a collection engine 504, a datastore integrity engine 506, and a data store 508 (e.g., data store 226).Generally, interoperability engine 502 receives data from elementswithin aggregation layer 304 (e.g., from aggregation engine 420) andperforms one or more operations with respect to the data.Interoperability engine 502 also facilitates storage of at least aportion of the processed information in data store 508.

Collection engine 504 is configured to generate message indicatorsidentifying flows of data by and between elements of an interactionsystem implemented using the techniques described herein. The flows ofinformation include messages which include data, and the messageindicators include unique message identifiers that can be used toidentify the messages. The unique message identifiers includeinformation that can be used to uniquely identify the messages. Forexample, a unique message identifier for a particular message caninclude a concatenation of the following information stored in a table:a source application, a facility, a message type, and a message controlidentification (ID). The unique message identifier can also be themessage control ID. The unique message identifier may be created asmessages including data are transmitted from aggregation layer 304.

In some examples, the table also includes information for tracking theprogress of the message from an origination node to a destination node.For example, typically when a message (e.g., any communication of data)is first received by transformative processing engine 108 (e.g.,interoperability engine 502), management engine 106 (e.g., collectionengine 504 of management engine 106) may generate a unique identifierfor the message in order to track that message as it moves throughoutthe interaction system. The unique identifier may be included in theheader of the message such that when the next node (e.g., component,device, server, etc.) after transformative processing engine 108receives the message, that node can report back to management engine 106that it saw the message. In this manner, management engine 106 may trackmessages from end-to-end for the life of the message.

In one example, the messages are requests. The requests may be generatedbased om user input at one of the components. The requests may bereceived by transformative processing engine 108 and integrated into thesystem. In some examples, management engine 106 may be notified that therequests have been received and may therefore be configured to generatemessage IDs for each request. These message IDs may then be associatedwith each of the requests. As the requests continue to move throughoutthe interaction system (e.g., away from transformative processing engine108), management engine 106 may track their movement using the messageIDs. If one of the requests does not arrive at its destination,management engine 106 may determine why the request was stopped. In someexamples, this cause may be hardware related (e.g., an unpluggedEthernet cable, a broken router, etc.), software related (e.g., a routerrouting to the wrong location), or any other reason for orders notarriving at their correct destination.

In some examples, management engine 106 (e.g., collection engine 504 ofmanagement engine 106) may receive the message and/or message identifierdirectly from one of components 410-418. For example, one of components410-416 may be configured to generate the unique message identifierand/or communicate directly with management engine 106. The message alsomay travel via one or more intermediate nodes on its way to thedestination node. In some examples, a node is a component such ascomponents 410-418, which may be running an application. In someexamples, the unique identifier and the routing of the message to itsdestination may be stored in a table that also includes: a geolocationof each node, a network from which the message originated, a type ofnode, the unique node identifier, and a time associated with the messageleaving the origination node. In some examples, collection engine 504provides unique message identifiers to other elements of the interactionsystem to monitor the messages as they move throughout the interactionsystem. Collection engine 504 also provides a portion of the uniquemessage identifiers to a management platform (indicated by a circle 528)for further analysis of the message identifiers. Such analyses mayinclude reconciliation of lost messages, latency reporting, auditmanagement and compliance, and other such analyses.

As mentioned previously, interoperability engine 502 is configured tostore data in data store 508. A plurality of sub-engines 510-516 ofinteroperability engine 502 are configured to perform operationsrelating to storing data in data store 508.

Interoperability engine 502 includes a tagging engine 510 configured toperform semantic tagging and indexing of data. Tagging engine 510therefore is configured to receive data, read metadata associated withthe data, semantically scan the content of the data, and associate oneor more tags with the data. Tagging engine 510 may therefore have accessto hundreds, thousands, or even more possible tags. These tags may havebeen input by users, learned, pre-defined, generated by outsidethird-party mapping sources, and/or gathered from other componentsand/or data stores of the interaction system. For example, if the datais a chart for an entity, the tagging engine may be configured to readany metadata associated with the chart to determine which tags may beappropriate to associate with the chart. From the metadata, taggingengine 510 may determine that the chart is for a type of entity byreading metadata indicating that an author field is populated with thename of another particular type of entity. Tagging engine 510 may haveaccess to other data to compare the analyzed metadata against (e.g., toidentify that the author's name corresponds to Dr. Brown who is anoncologist). Other examples, of metadata that may be included in one ormore fields include author, document type, creation time and date, lastupdate time and date, upload time and data, geographic location, uniqueID associated with the client or facility where the data originated, andother similar fields. The tags may be stored in association with thedata (e.g., the chart) and/or may be stored independent from the databut include an identifier such that when searching tags the data may becapable of population.

Continuing with the example from above, if the data is a chart for afirst type of entity, tagging engine 510 may be configured to read thecontent of the chart to determine which tags may be appropriate toassociate with the chart. For example, this may comprise analyzing thecontent of the chart (i.e., individual pages) semantically to look forartifacts (e.g., keywords, phrases, and the like) in the content. Theseartifacts may be identified by tagging engine 510 and used to decidewhich tags to associate with the document. In some examples, semanticscanning may involve filtering out words (e.g., articles, such as “a”and “the”), phrases, and the like. Similar to the reading of metadata,the tags may be pre-defined, user-defined, learned, and the like. Insome examples, reading metadata associated with messages may providemeaning and/or give context to the particular record of data. Thismeaning and/or context may assist tagging engine 510 to determine one ormore tags to associate with the data. The tags may be chosen, forexample, based on values of particular fields in the data, detecting afrequency of one or more words in a document or metadata and/or of a setof related words (e.g., tagging a record with “cancer” upon detectingwords such as tumor, metastasize, chemotherapy, radiation, oncology,malignant, stage 3, etc.). In this manner, tagging engine 510 may alsoindex portions of the data within one or more data stores of data store508. In some examples, such indexing may be based in part on theselected tags.

Interoperability engine 502 also includes a reports engine 512configured to generate one or more reports or alerts based on data. Forexample, reports engine 512 may generate reports when certain types ofdata are received or when data with certain characteristics is received.Reports engine 512 may also generate alerts. The reports and/or alertsgenerated by reports engine 512 may be outputted in the form of one ormore communications to an administrator, an authorized user, or othersimilar user via a user device. Such communications can include, forexample, signals, sirens, electronic notifications, popups, emails, andthe like. Content of such communications may include informationcharacterizing a performance metric, efficiency and/or outcomes;identifying concerning patterns; identifying losses of data; and thelike. In some examples, the content is presented in the form of one ormore documents, tables, figures, charts, graphs, and the like.

Interoperability engine 502 also includes a rules engine 514 configuredto create and manage condition-response rules, alert/reports rules,data-formatting rules, data-sharing rules, transmission rules,aggregation rules, user authorization rules, and other similar rules.Such rules may be user-defined, fixed, learned by elements of theinteraction system, and any combination of the foregoing. Finally,interoperability engine 502 includes an application engine 516configured to provide service-oriented architecture web services.

Data store 508 includes an electronic record information data store 518(“ERI data store 518”), a general data store 520, an operational datastore 522, an entity-based data store 524, and a streaming cachingstorage 526. While data store 508 is illustrated as including a fixednumber of data stores and storage elements, it is understood that datastore 508 can include any suitable number of data stores and storageelements, including more than illustrated or less than illustrated.

In some examples, a data query script is provided to query a first datastore and/or to obtain data for populating a data store. Such scriptcould query a data store described herein (e.g., data store 508) and/orcould be used to obtain data to populate a data store described herein(e.g., data store 508). In one instance, the script is configured to berepeatedly executed, so as to repeatedly draw data from a source datastore. The retrieved data can then be formatted, filtered, sorted and/orprocessed and then stored, presented and/or otherwise used. In thismanner, the script can be used to produce streaming analytics.

In some instances, the data query script, when executed, identifies eachof the data stores of interest. Identifying the data stores of interestinvolves identifying at least a portion of data from the data storessimultaneously and/or sequentially. For example, the script can identifycorresponding data stores (e.g., or components of a single data store ormultiple data stores) that pertain to one or more similar variables butthat differ in one or more other variables. Once the portion of the datafrom the data stores is identified, a representation of the identifieddata can be output to one or more files (e.g., Extensible MarkupLanguage (XML) files) and/or in one or more formats. Such outputs canthen be used to access the data within one or more relational databaseaccessible using Structured Query Language (SQL). Queries made using SQLcan be made sequentially or in parallel. Results from an SQL query maybe stored in a separate database or in an XML file that may be updatedeither in part or as a whole. The data query script may be executedperiodically, in accordance with a user-defined rule, in accordance witha machine-defined or machine-learned rule, and in other suitable manner.

Within ERI record data store 518 is retained data. In some examples, theinformation within ERI record data store 518 is organized according toentity identifying information. Thus, ERI record data store 518, in someexamples, includes individually identifiable information. But it mayalso include de-identified information.

Within general data store 520 is retained data. The data may be storedin a relational database format or in any other suitable format. Thus,the data within general data store 520 may be retained in a datastructure that includes one or more tables capable of accessing eachother. In some examples, general data store 520 includes a subset of theinformation that is included in operational data store 522.

Within operational data store 522 is retained data in a relationaldatabase format. Thus, the data within operational data store 522 may beretained in a data structure that includes one or more data structures(e.g., tables) capable of accessing each other. Operational data store522 is an example of an operational data warehouse. In operational datastore 522 is joined many different types of data. In some examples, theoperational data store 522 includes data pertaining to decision makingas discussed herein and other data typically used.

Within entity-based data store 524 is retained data in a non-relationaldatabase format. Thus, the data within entity-based data store 524 maybe retained in a structure other than tables. Such structure may beappropriate for large and complex data sets. In some examples,entity-based data store 524 (or any other data store) may be a unifiedsystem, which may include: a document-centric, schema-agnostic,structure-aware, clustered, transactional, secure, database server withbuilt-in search and a full suite of application services. An example ofsuch a unified system may be Marklogic. Entity-based data store 524 cansupport data aggregation, data organization, data indexing, data taggingand mapping to semantic standards, concept matching, concept extraction,machine learning algorithms, concept discovery, concept mining, andtransformation of record information. In some examples, entity-baseddata store 524 includes data pertaining to decision making (similar togeneral data store 520) as discussed that is organized and accessed in adifferent manner. For example, the data within entity-based data store524 may be optimized for providing and receiving information over one ormore information exchanges. In some examples, entity-based data store524 includes a subset of the information that is included in operationaldata store 522.

Finally, in some examples, streaming caching storage 526 is a streamingdata cache data store. As discussed previously, certain components ofcomponents 410-418 may support streaming data to other components oruser devices. Streaming caching storage 526 is a location wherestreaming data can be cached. For example, assume that component 418 isa piece of equipment operating at Location A and that a user using acomputer in Location B desires to view a live of substantially livestream of outputs of the piece of equipment. Component 418 can send aportion of data to streaming caching storage 526 which can retain theportion of the data for a certain period of time (e.g., 1 day). Thus,streaming caching storage 526 is configured to cache data that can bestreamed.

Diagram 500 also includes data store integrity engine 506. In someexamples, data store integrity engine 506 is configured to ensureintegrity of the information within data store 508. For example, datastore integrity engine 506 applies one or more rules to decide whetherinformation within all or part of data store 508 should be scrubbed,removed, or adjusted. In this manner, confidence is increased that theinformation within data store 508 is accurate and current.

FIG. 6 shows a diagram 600 which depicts a portion of architecture stack300 according to at least one example. In particular, the diagram 600includes access management layer 310, audit/compliance layer 312, agencylayer 314, and a portion of interface layer 316.

Access management layer 310, as illustrated in the diagram 600, includesan access management engine 602. Access management engine 602 is anexample of access management engine 222. Generally, access managementengine 602 can be configured to manage access to elements oftransformative processing engine 202 by different components,applications, and user devices.

Access management engine 602 within access management layer 310 alsoprovides functionality similar to an operating system. For example,access management engine 602 includes a plurality of engines configuredto manage different aspects of interacting with elements of theinteraction system. For example, a user who desires to access portionsof data retained in data store 508, may do so by interacting with accessmanagement engine 602 using one or more applications (not shown). Thus,access management engine 602 includes a variety of engines to enablesuch interaction. The engines include, for example, an authenticationaccess engine 604, a login engine 606, a user preference engine 608, asecurity engine 610, an analytics and search engine 612, a data accessengine 614, an update engine 616, and a streaming data engine 618. Thedifferent engines of access management engine 602 can define routines,protocols, standards, and the like for interacting with elements of theinteraction system.

Beginning first with authentication access engine 604, authenticationaccess engine 604 evaluates the rules and conditions under which usersmay access elements of the interaction system; in particular, theconditions under which users may access data within data store 508.These rules and conditions may be user-defined (e.g., by anadministrator or reviewer), learned over time, and/or may be dynamicallyupdated and/or evaluated based on characteristics of the user or theuser's device attempting to access the interaction system. The rules andconditions may indicate the types of users who have particular types ofaccess within the interaction system. The type of access may also relateto the degree to which data is identified/de-identified. In someexamples, a user desiring access to data provides certain identifyinginformation and authentication access engine 604 authenticates anidentity of the user.

Login engine 606 evaluates the rules and conditions under which usersare able to log in to the interaction system or access applicationsassociated with the interaction system. These rules and conditions maybe user-defined (e.g., by an administrator), learned over time, and alsomay be dynamically updated and/or evaluated based on characteristics ofthe user or the user's device attempting to access the interactionsystem. Thus, while authentication access engine 604 evaluates the rulesto determine which users may access the interaction system, login engine606 evaluates the particular credentials, profiles, etc. of the users.For example, login engine 606 can confirm that an entered username(e.g., and password), provided biometric data or code or identifier in ascanned tag or badge matches that in an authorized user data structure.

Login engine 606 evaluates one or more user profiles associated witheach authenticated user. In some examples, a user profile includes ausername, password, and other information associated with the user. Forexample, a user profile may indicate characteristics about the user.

User preference engine 608 evaluates the rules and conditions underwhich user are able to store and update one or more user preferencescorresponding to access of the interaction system or access toapplications associated with the interaction system. These rules andconditions may be user-defined (e.g., by the user or administrator), andmay include rules for default preferences. For example, using userpreference engine 608, a user may indicate a format in which the userprefers to receive outputted information, display characteristics of agraphical user interface associated with the user, and other similaruser preference settings. For example, the user may indicate thatcertain types of reports and/or alerts are to be sent to the user.

Security engine 610 evaluates the rules and conditions for ensuring thesecurity of access to the elements of the interaction system. In someexamples, these rules and conditions are determined by administrators ofthe interaction system. In some examples, security engine 610 provides aplurality of computer virus protection services. These services can becalled up and implemented when accessing the interaction system oraccessing applications associated with the interaction system. The rulesand conditions may be based on roles, based on profiles, based ondomains, and any other suitable security configuration. For example,because the interaction system may include sensitive data, securityengine 610 may enforce a domain-based rule that protects certainsensitive information (e.g., identifying information).

Analytics and search engine 612 evaluates the rules and conditions underwhich users can search for data within the interaction system and accessanalytics relating to the interaction system. In some examples, theserules and conditions are user-defined or learned over time in accordancewith search engine optimization techniques. For example, analytics andsearch engine 612 is used to search within data store 508 for particulardata. Analytics and search engine 612 supports any conventionalsearching algorithms. For example, search engine 612 can be used tosearch within various fields and potential field values. In someexamples, search engine 612 can provide analytics, such as statistics,graphs, distributions, and/or comparative analysis pertaining toparticular entities and/or characteristics. Such information may beselected by a user and presented on a user interface.

Data access engine 614 evaluates the rules and conditions under whichusers may operation in order to access particular data within data store508. In some examples, these rules and conditions are user-defined orlearned over time. For example, data access engine 614 may indicate theroutines, subroutines, or other logic needed for an application toaccess certain portions of data store 508. For example, whileauthentication access engine 604 and login engine 606 may manage whichusers can access parts of the interaction system, data access engine 614may manage how authenticated users access data within data store 508. Tothis end, data access engine 614 may enforce and/or evaluate certainrules managing how users access different components of the interactionsystem. In some examples, data access engine 614 may be used to actuallyaccess data within data store 508 (e.g., extract, download, or otherwiseaccess). In some examples, data access engine 614 may define procedures,protocols, and the like for accessing data. The protocols and proceduresfor accessing data access engine 614 (like the other engines of accessmanagement engine 602) may be provided to developers in the form of asoftware development kit (SDK). SDKs may enable developers writeapplications that can effectively communicate with elements (e.g., datastore 508) of the interaction system. In particular, applications thatcan access a portion of the data stored within active unified data layer308.

Update engine 616 evaluates the rules and conditions for providingupdates to other engines within access management engine 602, plug-insfor applications that access the interaction system, and for othersimilar elements of the interaction system. For example, updates may begenerated at runtimes, at defined time intervals, upon request by auser, upon receiving a threshold quantity of new or changed data. Oncean update is performed, an interface may be refreshed, a report may besent indicating that the update was successful or unsuccessful, or thelike.

Streaming data engine 618 defines the rules and conditions for enablingstreaming of data between components and user devices of the interactionsystem. For example, streaming data engine 618 may enable component 414to stream data. Streamed data may include live or substantially liveaudio or video feeds, results of tests, output from equipment ordevices, and any other suitable type of data capable of being streamed.In some examples, the data may be streamed to other components or userdevices within the network or outside the network. In order to establisha streaming transmission, streaming data engine 618 may identify astreaming destination and a streaming origin. Next, streaming dataengine 618 may pair the two and enable streaming. This may includeallocated bandwidth within one or more network devices associated withthe interaction system. Streaming data engine 618 may also adjust thequality of the streaming data based on the availability of bandwidth. Insome examples, streaming data engine 618 may receive incoming streams(and continuously present the stream or monitor for particular data(e.g., exceeding a threshold, exhibiting an above-threshold change,having a particular value)).

Within audit/compliance layer 312 is located an access log engine 622.Access log engine 622 evaluates the rules and conditions for loggingaccess to the interaction system by users, applications, devices, andthe like. Logging access includes, in some examples, logging dataconventionally collected by access log engines running in similarenvironments. Access log engine 622 can use this data to generate andtransmit reports, for example, to stakeholders of the interaction systemsuch that they can make informed decisions regarding that is accessingthe interaction system and for what purposes.

Within agency layer 314 is located an agency engine 624. Agency engine624 evaluates the rules and conditions under which agencies can accessthe interaction system. In some examples, agency engine 624 may be usedto track one or more performance indicators identified by a governmentagency and/or to provide report instances of defined types of events. Insome examples, a university is an agency that uses agency engine 624 tocollect data pertaining to one or more studies. Agency engine 624 cancollect the pertinent data, potentially format and/or analyze the data,and facilitate transmission of the data to the appropriate agency.

FIG. 7 shows a diagram 700 which depicts a portion of architecture stack300 according to at least one example. In particular, diagram 700includes interface layer 316, and application/device layer 320. Withininterface layer 316 is located interface engine 702 (e.g., interfaceengine 224). Interface engine 702 is configured to generate one or moreinterfaces (e.g., graphical user interface 726, programmatic interface728, and/or web interface 730) to enable data to flow to user devices710, 712, and 714 via respective applications 720, 722, and 724. In someexamples, the interfaces of interface engine 702 are embodied inhardware, software, or some combination of both. Within interface layer316 communications and inputs directed to interacting with elements ofaccess management layer 310 may be embodied.

Graphical user interface 726 is any suitable graphical user interfaceconfigured to interact with elements of the interaction system.Programmatic interface 728 includes an application programminginterface, a programmatic user interface, and other similar interfacesfor defining core functions for accessing elements of the interactionsystem. For example, programmatic interface 728 may specify softwarecomponents in terms of their operations. Web interface 730 is anysuitable web interface configured to interact with elements of theinteraction system. Any of the interfaces described herein may beconfigured to receive user input, present dynamic presentations thatdepend on user input, and otherwise respond to user input. In someexamples, such input may be provided via one or more input devices(e.g., a keyboard, touchscreen, joystick, mouse, microphone, devicescapable of capturing inputs, and the like) operated by one or more usersof user devices 706-714. Output may be provided via one or more outputdevices (e.g., a display or speaker).

Interface engine 702 is utilized by applications internal to theinteraction system and external to the interaction system to accessdata. In some examples, the applications that are internal includeapplications that are developed for internal use by various entitiesassociated with the interaction system. In some examples, theapplications that are external to the interaction system includeapplications that are developed for external use by those that are notassociated with the interaction system.

Generally, within application/device layer 320, applications 716-724which communicate with other elements of architecture stack 300 usingthe interfaces generated by interface engine 702 are defined. Thisincludes detailing how applications 716-724 are to interact with theinterfaces generated by interface engine 702 for accessing data. Forexample, interacting may include accepting inputs at user devices706-714 to access data and, in response, providing the data, prompts, orother types of interaction with one or more users of the user devices706-714. Thus, applications 716-724 may be related to one or more of theinterfaces generated by interface engine 702. For example, application720 may be interact with a graphical user interface (whether generatedby interface engine 702 or otherwise) to interact with other elements ofthe interaction system. Interacting may include receiving inputs at thegraphical user interface via application 720, providing output data tothe graphical user interface application 720, enabling interaction withother user devices, other applications, and other elements of theinteraction system, and the like. For example, some of the inputs maypertain to aggregation of data. These inputs may include, for example,types of data to aggregate, aggregation parameters, filters ofinterested data, keywords of interested data, selections of particulardata, inputs relating to presentation of the data on the graphical userinterface, and the like. Providing output data may include providing theaggregated data on the graphical user interface, outputting theinformation to one of the other user devices 706-714 running one of theother applications 716-724.

Turning now to the details of applications 720, 722, and 724. In someexamples, applications 720, 722, and 724 include a variety of differentapplications that can be designed for particular users and/or uses. Inone example, application 720 includes dashboards, widgets, windows,icons, and the like that are customized for a particular entity. In someexamples, application 720 may present different data depending on afocus of the entity and protected information associated with theentity. In this manner, application 720 adapts and automatically adjustsdepending on the context in which the entity is using the application.Application 720 may be configured to receive input, adjustpresentations, present unprompted alerts, adjust display of content,move more relevant content to the foreground, move less relevant contentto the background, and/or populate forms for the entity.

In another example, application 722 may be specific for nurses or typesof nurses. In this example, application 722 may include dashboards,widgets, windows, icons, and the like that are customized to individualnurses. Similar to the example discussed above pertaining to the user,in some examples, application 724 may present different data dependingon a position of the nurse. In this manner, application 722 adapts andautomatically adjusts depending on the context in which the nurse isusing the application. For example, the nurse may receive data, such astest results.

In some examples, application 724 may be a multi-role application foradministrators and is used to manage entities constitute the populationof the entities or organizations within the interaction system. Similarto the other examples discussed, in some examples, application 724 maypresent different data depending on a role of the user who is usingapplication 724. In this manner, application 724 adapts andautomatically adjusts depending on characteristics of the user who isusing application 724. In this manner, application 724 can providedifferent data depending on the role of the user. For example, whetherdata presented includes identifiable or de-identified information maydepend on a position of the user.

Applications 716 and 718 shown in connection with interface engine 702are applications developed by third-parties. In some examples, suchapplications include any suitable application that benefits fromaccessing data. The interaction system may include data pertaining tohundreds of thousands of entities. Having data pertaining to so manyentities presents security concerns. For example, much of the data maybe identifying data. Accordingly, data that may be accessed byapplications 716 and 718 may be limited. In some examples, an entity ofthe interaction system may use one of applications 716, 718 to accesshis or her own data. In this example, the identity of the entity may beverified in accordance with techniques described herein.

User devices 706-714 are any suitable user devices capable of runningapplications 716-724. User devices 706-714 are examples of the userdevice 228. In some examples, the user devices include: mobile phones,tablet computers, laptop computers, wearable mobile devices, desktopcomputers, set-top boxes, pagers, and other similar user devices. Insome examples, at least some of user devices 706-714 are the samedevices as at least some of the one or more components 410-418. In someexamples, user devices 706-714 may include complementary layers toapplication/device layer 320 and/or receiving layer 302. For example,user devices 706-714 may include a transmission layer, a generationlayer, and/or a receiving layer to communicate data atapplication/device layer 320 and at receiving layer 302.

Turning now to FIG. 8, an interaction system 800 is shown according toat least one example. Interaction system 800 includes an internalorganization 822 including a transformative processing engine 802. Thetransformative processing engine 802 is an example of transformativeprocessing engine 202 previously discussed. Interaction system 800 isillustrated as an example configuration for implementing the techniquesdescribed herein. In particular, a configuration of elements asillustrated in FIG. 8, at least in some examples, communicates accordingto the layers of architecture stack 300. For example, internalorganization 822 includes generation components 804(1), 804(2), and804(N) which provide data to aggregation servers 806(1)-806(N).

Generation components 804(1), 804(2), and 804(N) operate in accordancewith receiving layer 302. In some examples, generation component 804(1)is a piece of equipment, generation component 804(2) is computer with adata collection device, a type of lab system, and generation component804(N) is a terminal. Aggregation servers 806(1)-806(N) operate inaccordance with aggregation layer 304. Aggregation servers 806(1)-806(N)share data with data storage servers 808(1)-808(N) via one or moreinternal network(s) 810. In some examples, internal network 810 is anysuitable network capable of handling transmission of data. For example,internal network 810 may be any suitable combination of wired orwireless networks. In some examples, internal network 810 may includeone or more secure networks. Data storage servers 808(1)-808(N) areconfigured to store data in accordance with active unified data layer308. Data storage servers 808(1)-808(N) include database servers, filestorage servers, and other similar data storage servers.

Access management servers 812(1)-812(N) manage access to the dataretained in the data storage servers 808(1)-808(N). Access managementservers 812(1)-812(N) communicate with the other elements of interactionsystem 800 via internal network 810 and in accordance with accessmanagement layer 310.

Interface servers 814(1)-814(N) provide one or more interfacesapplications to interact with the other elements of interaction system800. Interface servers 814(1)-814(N) provide the one or more interfacesand communicate with the other elements of interaction system 800 viainternal network 810 and in accordance with interface layer 316. Theinterfaces generated by the interface servers 814(1)-814(N) can be usedby internal user devices 816(1)-816(N) and external user devices 818(1),818(2), and 818(N) to interact with elements of interaction system 800.

Internal user devices 816(1)-816(N) are examples of user devices706-714. In some examples, internal user devices 816(1)-816(N) runapplications via the interfaces generated by interface servers814(1)-814(N). As an additional example, external user devices 818(1),818(2), and 818(N) can run applications developed by third parties thataccess the other elements of interaction system 800 via the interfacesgenerated by interface servers 814(1)-814(N).

External user devices 818(1), 818(2), and 818(N) access the interfacesvia external network 820. In some examples, external network 820 is anunsecured network such as the Internet. External user devices 818(1),818(2), and 818(N) are examples of user devices 706-714. External userdevice 818(1) is a mobile device. In some examples, the mobile devicemay be configured to run an application to access interaction system800. Similarly, the other external user devices 818(2)-818(N) runapplications that enable them to access interaction system 800. Whileinteraction system 800 is shown as implemented using discrete servers,it is understood that it may be implemented using virtual computingresources and/or in a web-based environment.

The systems, environments, devices, components, models, and the like ofFIGS. 1-8 may be used to implement a particular system as describedherein with reference to later figures. In one example, a computer-basedmethod is provided for aggregating data from a multitude of disparatesources and using the data to customize a user interface. An aggregationengine may derive time record from data stored by a multitude ofdisparate sources including, for example, a database that storesreserved block data (e.g., scheduling data that indicates times at whichusers are scheduled for performing activities such as working an 8-hourshift), a database that stores activity event data (e.g., punch clockdata that is associated with the users and is collected from time clocksat which the users “punch” in and out of work), and a database thatstores exchange condition data (e.g., may include the types of hoursthat each user is qualified to work, such as productive time, secondshift time, overtime, etc.). The aggregation engine predicts whether theuser is on pace to meet or exceed her expected schedule (e.g., get extracompensation) and updates a user interface with this information. Thisenables an authorized user to adjust the reserved blocks for the usersin order to avoid extra compensation. The aggregation engine alsoidentifies instances when the users may be accruing extra time by latepunches, early punches, and punches occurring in non-home departments. Anotification engine takes information generated by the aggregationengine and generates and send notifications to the relevant authorizedusers (e.g., administrators, managers, etc.).

The techniques described herein constitute one or more technicalimprovements to the systems and devices on which the techniques areperformed. For example, physical storage medium space is conservedbecause instead of multiple users exporting, downloading, and storinglarge files from different systems as conventionally done, thetechniques described herein obtain the raw data directly from the sourcesystems, process the data on the fly, and present it in a streamlineduser interface that is accessible by the multiple users. Additionally,bandwidth resources are conserved because, unlike the conventional formof multiple users sharing via email (e.g., a first user downloading andemailing to other users), the techniques described herein obtain the rawdata as described above and make it accessible via the user interface.Additionally, user time and effort of reviewing records of other usersis reduced given the streamlined user interface, described herein.

Referring now to FIG. 9, FIG. 9 illustrates a block diagram of anexample aggregation system 900, according to at least one example. Theaggregation system 900 includes a server system 902 including anaggregation engine 904 and a general datastore 906, a user device 908, apresentation engine 910, a plurality of data stores 912-918, a rulesanalysis engine 920, and a notification engine 922.

Generally, the aggregation engine 904 (e.g., an example of theaggregation engine 218), which may include any suitable combination ofsoftware and/or hardware, is configured to collect data from varioussources and to perform one or more operations on the collected data. Forexample, the aggregation engine 904 may aggregate reserved block datafrom a reserved block data store 912, activity event data from anactivity event data store 914, exchange condition data from an exchangecondition data store 916, and user data from a user data store 918. Thedata stores 912-918 are examples of data sources and may include anysuitable combination of hardware and/or software capable of storingdata. In some examples, one or more of the data stores 912-918 aredatabase. The data in the data stores 912-918 may be of any suitabletype such as relational, graphical, and the like, depending on theimplementation. In some examples, at least one of the data stores912-918 may take a different form such as a remote resource, the data ofwhich is accessed using an application programming interface.

In some examples, the reserved block data store 912 may be part of acomputer system that is separate from the server system 902. Forexample, the reserved block data store 912 may be maintained by acomputer system (or computer application) dedicated to managingreservation of time blocks. The server system 902 is able to retrievedata from the reserved block data store by virtue of a networkconnection between the reserved block data store 912 and the serversystem 902. In some examples, the server system 902 and the computersystem that manages the reserved block data store are operated by thesame entity.

The reserved block data store 912 stores reserved block data such as alist of users who are scheduled to work at a facility on a particularday. The reserved block data may also include the start time and the endtime of each user's shift, along with the start time and the end time ofany scheduled breaks, and/or the expected quantity and duration of anybreaks. In addition, the reserved block data may include informationregarding the times when various rooms and equipment are expected to bein use. Further, the reserved block data may include a list of thedependent users (e.g., patients) who have a scheduled event at thefacility, along with a description of each dependent user's conditionand scheduled procedure. In other examples, such as emergency rooms andurgent care facilities, the reserved block data may include predictionsof the conditions and procedures of dependent users who are likely toarrive that day. For example, machine learning techniques may be used toanalyze historical data and generate predictions based on variousfactors, such as day of the week, time of the day, weather conditions,traffic patterns, crime rates, etc.

In some examples, the activity event data store 914 may be part of acomputer system that is separate from the server system 902. Forexample, the activity event data store 914 may be maintained by acomputer system (or computer application) dedicated to collecting,sorting, and storing activity events. The server system 902 is able toretrieve data from the activity event data store 914 by virtue of anetwork connection between the activity event data store 914 and theserver system 902. In some examples, one entity may operate the serversystem 902 and the computer system that manages the activity event datastore 914.

The activity event data store 914 stores activity event data such asrecords of time card punches made at various punch clocks within anorganization. The punch clocks may be manual or electronic, and thepunch clock data may indicate which punch clock was used for each timecard punch. In other examples, the activity event data may includerecords of when a user entered or left an area based on wirelesstransmissions from an application on the user's smartphone, badge, etc.Any suitable wireless communication technology may be used, such asWiMAX, WiFi, radio, cellular networks, etc.

In some examples, the exchange condition data store 916 may be part of acomputer system that is separate from the server system 902. Forexample, the exchange condition data store 912 may be maintained by acomputer system (or computer application) dedicated to managing exchangeconditions. The server system 902 is able to retrieve data from theexchange condition data store 916 by virtue of a network connectionbetween the exchange condition data store 916 and the server system 902.In some examples, one entity operates the server system 902 and thecomputer system that manages the exchange condition data store 916. Insome examples, a first entity may operate the server system 902 and thecomputer system that manages the reserved block data store 912 and asecond entity may operate the activity event data store 914 and theexchange condition data store 916.

The exchange condition data store 916 may store exchange condition datasuch as the types of hours that each user is qualified to work, such asproductive time, second shift time, overtime, etc. The exchangecondition data may also include information about how to compensate eachuser for each time block that the user works. For example, a normalshift may be paid at an agreed rate, but if the user works longer, theuser may be paid at 1.5 times the agreed rate. The exchange conditiondata may be determined by a rule analysis engine 920. The rules analysisengine 920 evaluates the exchange condition data and determines whetherchanges should be made. The rules analysis engine 920 also provides auser interface for a user to input changes to the exchange conditiondata.

In some examples, the user data store 918 may be part of a computersystem that is separate from the server system 902. For example, theuser data store 918 may be maintained by a computer system (or computerapplication) dedicated to managing user data. The server system 902 isable to retrieve data from the user data store 918 by virtue of anetwork connection between the user data store 918 and the server system902. In some examples, one entity operates the server system 902 and thecomputer system that manages the user data store 918. In some examples,a first entity may operate the server system 902 and the computer systemthat manages the reserved block data store 912 and that manages the userdata store 918, and a second entity may operate the activity event datastore 914 and the exchange condition data store 916.

The user data in the user data store 918 may include various informationabout each user, such as the user's general qualifications and anyspecific tasks that the user is qualified to perform. For example, theuser data may indicate which equipment an user is qualified to operateand which procedures the user is qualified to perform. In some examples,the user data may be used to store user profiles for each of the users.The user profiles may identify characteristics, qualifications,certifications, demographics, and any other suitable contextualinformation. In some examples, each user profile may include a useridentifier that uniquely identifies the user.

The reserved block data, activity event data, exchange condition data,and user data may be updated periodically, such as every minute, everythirty minutes, every hour, every two hours, every four hours, daily,weekly, or monthly. Further, the reserved block data, activity eventdata, exchange condition data, and user data may be sent to theaggregation engine 904 periodically, such as every minute, every thirtyminutes, every hour, every two hours, every four hours, daily, weekly,or monthly. In some examples, the server system 902 is able to outputnotifications and/or provide new data to a rendered user interface every15 minutes. This may mean that the aggregation engine 904 collects newdata from at least some of the data stores 912-918 as often as every 15minutes.

The aggregation engine 904 may aggregate some or all of the data. Theaggregation engine 904 may include various engines for aggregating thedata. After aggregating the data, the aggregation engine 904 may sendthe results to a general data store 906, which is configured to storethe results. Further, the aggregation engine 904 may output the resultsto the notification engine 922 and/or the rendering engine 910. Thenotification engine 922 is configured to generate notificationsregarding output from the aggregation engine 904. Such notifications mayinclude anomaly events identified by the aggregation engine 904. Thenotifications may be provided to the user device 908 for consumption. Insome examples, when the results are provided to the rendering engine910, the rendering engine 910 may generate a user interface thatincludes the results, as described with respect to FIGS. 12-17.

FIG. 10 is an example diagram illustrating an aspect of a system 1000 inwhich techniques relating to aggregating data from disparate datasources for user interface customization may be implemented, accordingto at least one example. The system 1000 includes components from thesystem 900 such as the data stores 912-918, the aggregation engine 902and the rendering engine 910. The system 1000 in particular is used todetermine a proactive holistic view of the time data.

Generally, the system 1000 depicts a flow of data from the data stores912-918 to the aggregation engine 902, and from the aggregation engine902 to the rendering engine 910, which generates an output 1002. Theaggregation engine 902 begins by determining an ideal schedule 1004using data received from the reserved block data store 912. The idealschedule 1004 may indicate reserved blocks of time for a user withinsome time period (e.g., a day, a week, a month, etc.). An ideal schedule1004 may be determined for each user of the system, i.e., on auser-by-user basis. In some examples, the ideal schedule 1004 isgenerated by a different system and stored by the reserved block datastore 912 and accessed by the aggregation engine 902. The renderingengine 910 receives the ideal schedule 1004 and renders a timeline thatidentifies the scheduled, i.e., reserved blocks as the output 1002. Insome examples, the timeline may be 35 hours and/or otherwise correspondto the period defined above.

The aggregation engine 902 also determines an actual schedule 1006 usingdata received from the activity event data store 914. The data receivedfrom the activity event data store 914 may include a record of activityevents that identify a user and a location and/or device at which theactivity event was recorded, along with a timestamp. The aggregationengine 904 uses this data to determine the actual schedule 1006 on auser-by-user basis, i.e., for each user in the system 1000. The actualschedule 1006 is an accurate reflection of when the user was performingthe activities, i.e., when the user punched in and punched out duringsome predefined period. The actual schedule 1006 may correspond to sometime period (e.g., a day, a week, a month, etc.). In some examples, theactual schedule 1006 is generated by a different system and stored bythe activity event data store 914 and accessed by the aggregation engine902. The rendering engine 910 receives the actual schedule 1006 andrenders user interface elements that include a timeline that identifiesthe actual blocks, i.e., blocks bounded by two activity events (e.g., apunch in and a punch out) as the output 1002. In some examples, thetimeline may be 35 hours and/or otherwise correspond to the perioddefined above.

The aggregation engine 902 uses the ideal schedule 1004 and the actualschedule 1006 to compute exceptions 1008. The exceptions 1008 identifyinstances when the actual schedule 1006 is different from the idealschedule 1004. Thus, the exceptions 1008 may include many differentcircumstances such as when the actual schedule 1006 includes actualblocks that were not approved (i.e., not reflected on the ideal schedule1004), that were late or early with respect to the reserved blocks inthe ideal schedule 1004, that overlap with other time, that werecollected in a non-home department, etc. The exceptions 1008 are sharedwith the rendering engine 910, which renders user interface elementsthat represent the exceptions 1008, as illustrated in later figures. Therendering engine 910 provides the user interface elements 910 as theoutput 1002.

The aggregation engine 902 also determines exchange conditions 1010 byaccessing exchange condition data from the exchange condition data store916. In some examples, the computer system that manages the exchangecondition data store 916 and/or the rules analysis engine 920 determinesthe exchange conditions 1010 and stores them in the exchange conditiondata store 916. The exchange conditions 1010 are then aggregated at 1012by the aggregation engine 902 and shared with the rendering engine 910.The aggregated exchange conditions may include organizing the exchangeconditions 1010 by group and calculating a group start offset and widthof user interface elements used to represent the exchange conditions1010 in the output 1002.

The aggregation engine 902 also access the user data 1014 from the userdata store 908 and shares the user data 1014 with the rendering engine910. In some examples, the ideal schedule 1004, the actual schedule1006, and the exchange conditions 1010 may be associated with a userprofile record of a user stored in the user data store 918 andrepresented by the user data 1014. This may enable the rendering engine910 to display the correct data in connection with the correct user.

FIG. 11 is an example diagram illustrating an aspect of a system 1100 inwhich techniques relating to aggregating data from disparate datasources for user interface customization may be implemented, accordingto at least one example. The system 1100 includes components from thesystem 900 such as the data stores 912-918, the aggregation engine 902,the notification engine 922, and the user device 908. The system 1100 inparticular is used to analyze the data of the system to determineincremental increases in the user's actual time. The incrementalincreases may be characterized in minutes such as incremental 15minutes, incremental 30 minutes, incremental 45 minutes, etc.

Generally, the system 1100 depicts a flow of data from the data stores912-918 to the aggregation engine 902, and from the aggregation engine902 to the notification engine 922, which sends notifications to theuser device 908. The aggregation engine 902 begins by determining ahistorical schedule 1102 using data received from the reserved blockdata store 912. The historical schedule 1102 may include reserved blocksin the past, which is based on the ideal schedule 1004. In someexamples, the aggregation engine 902 may access the historical schedule1102 directly from the reserved block data store 912.

The aggregation engine 902 also determines historical activity events1104 using data received from the activity event data store 914. Thehistorical activity events 1104 may include actual blocks that occurredin the past, which is based on the actual schedule 1006. In someexamples, the aggregation engine 902 may access the historical activityevents 1104 directly from the activity event data store 914.

The aggregation engine 902 then, at 1106, combines the historicalschedule 1102 and the historical activity events 1104. This may includecomparing the historical schedule 1102 and the historical activityevents 1104 to determine any discrepancies.

The aggregation engine 902 also determines exchange conditions 1108using data received form the exchange condition data store 916. Theexchange conditions 1108 are an example of the exchange conditions 1010.

The aggregation engine 902 then, at 1110, validates accrual of theblocks represented by the combination of the historical schedule 1102and the historical activity events 1104, and the exchange conditions1108. Validating the accrual may include rounding times in thehistorical activity events 1104, which represent an actual schedule, andsubtracting the historical schedule 1102, which represents an idealschedule, from the rounded times. Depending on the difference, thenotification engine 922 may generate different notifications which maybe sent to different user devices 908. The notification engine 922 alsoshares a notification history 1112 regarding what notifications itgenerated with the aggregation engine 902 to send back to the generaldata store 906. In this manner, a record of notifications is stored inthe general data store 906.

Similar to the discussion above of determining accrual of blocks, thesystem 1100 may be used to determine accrual of overtime. This may beused to determine whether, given a set of actual blocks represented bythe historical activity events 1104 and a set of reserved blocksrepresented by the historical schedule 1102, a user is at risk ofexceeding some predefined value represented as a threshold or value(e.g., a threshold number of hours resulting in a differentarrangement). In some examples, there may be a set of thresholdsrelating to a given major threshold (e.g., 40 hours). For example, afirst threshold may be 40 hours (e.g., the same as the major threshold),indicating that a user is already exceeded the major threshold. A secondthreshold may be more than 32 hours, indicating that a user is at riskof exceeding the major threshold. A third threshold may be less than 32hours, indicating that a user is not at risk of exceeding the majorthreshold. This process may be run towards the end of a given period(e.g., week). In some examples, the thresholds can be adjusted and theprocess associated with the system 1100 can be executed daily.

FIG. 12 is an example diagram illustrating a user interface 1200 thathas been customized with data aggregated from disparate sources,according to at least one example. The user interface 1200 is depictedin a web browser 1202 on a display device. The user interface 1200 inparticular depicts data for an entire region, “Far North.” The userinterface 1200 includes a data section 1204, a facility section 1206that identifies facilities, and a filtered data section 1240.

The data section 1204 include a plurality of sub-sections 1208-1222,each of which includes at least one box including the number of recordscorresponding to a section definition. At least some of the data in thesub-sections 1208-1222 is computed by the aggregation engine 902, whileat least some of the data is pulled directly from the data stores912-918. The sub-section 1208 represents a total number of users in theregion. The sub-section 1210 represents a total number of emailnotifications sent within the region. These email notifications mayrelate to those sent by the notification engine 922 of the system 902.

The sub-section 1212 represents activity event data, at least some ofwhich has been processed by the aggregation engine 902 using thetechniques described herein. In particular, the sub-section 1212includes instances when users do not record activity events, recordactivity events early, record activity events late, record activityevents in a non-home department, and/or are contract users.

The sub-section 1214 represents reserved block data, at least some ofwhich has been processed by the aggregation engine 902 using thetechniques described herein. In particular, the sub-section 1214includes the number of approved reserved blocks, the number ofunscheduled, and the number of users that transferred from on-call to onthe clock.

The sub-section 1216 represents output that has been processed by theaggregation engine 902 using the techniques described herein. Inparticular, the sub-section 1216 includes the number of short and longlunches, meals, and breaks that are exceptions.

The sub-section 1218 represents output that has been processed by theaggregation engine 902 using the techniques described herein. Inparticular, the sub-section 1218 includes the number of users whosehours have already exceeded a major threshold for a given period, atrisk of exceeding the major threshold for the given period, or are notat risk of exceeding the major threshold.

The sub-section 1220 represents output that has been processed by theaggregation engine 902 using the techniques described herein. Inparticular, the sub-section 1220 includes incremental time that has beencaptured by the users.

The sub-section 1222 represents exchange condition data, at least someof which has been processed by the aggregation engine 902 using thetechniques described herein. In particular, the sub-section 1222includes different exchange classes of users.

Generally, the filtered data section 1240 includes the same datarepresented by the data section 1204, but organized/filtered byfacility. In some examples, each column in the filtered data section1240 may correspond to one of the definitions associated with the boxesin the data section 1204. For example, the column 1224 may correspondthe number of early activity events represented by sub-section 1212. Thecolumn 1226 may correspond to the number of late activity eventsrepresented by the sub-section 1212. The column 1228 may correspond tothe number of activity events (and/or users) that recorded activityevents in a non-home department. The columns 1230-1234 may correspond toincremental time represented by the sub-section 1220. The column 1236may correspond to users that have already exceeded the major threshold,as represented by the sub-section 1218. Similarly, the column 1238 maycorrespond to users that are at risk of exceeding the major threshold,as represented by the sub-section 1218.

Any of the boxes in the data section 1204, the filtered data section1240, and/or the facility section 1206 is selectable and may enablefurther drilling down into the underlying data. Similarly, selection ofany of the facilities may enable drilling down to a facility level.

FIG. 13 is an example diagram illustrating a user interface 1300 thathas been customized with data aggregated from disparate sources,according to at least one example. The user interface 1300, which is anexample of the user interface 1200, is depicted in a web browser 1302 ona display device. The user interface 1300 in particular depicts data foran entire region, “Far North” over a full month. Like the user interface1200, the user interface 1300 includes a data section 1304, a facilitysection 1306 that identifies facilities, and a filtered data section1340.

As may be apparent, because of the full month time period, the number ofrecords in the data section 1304 and the filtered data section 1340 ismuch larger than illustrated in FIG. 12. Because of the additional data,the aggregation engine 902 is able to determine and display trendingdata (e.g., a miniaturized but technically accurate graph) in connectionwith each of the totals in the boxes in the filtered data section 1340.When hovering over one of the boxes, the trending data may be presentedin a popup window 1342. In this example, the trending data may be agraph of the underlying data associated with the particular cell, i.e.,at the “Good Health” facility and “none” in the activity from thesub-section 1312. The trending data is trending data at a facilitylevel.

FIG. 14 is an example diagram illustrating a user interface 1400 thathas been customized with data aggregated from disparate sources,according to at least one example. The user interface 1400, which is anexample of the user interface 1300, is depicted in a web browser 1402 ona display device. The user interface 1400 in particular depicts data foran entire facility, “Good Health” over a full month. For example, a usermay have selected the “Good Health” facility from the list in thedepartment section 1406. Like the user interface 1300, the userinterface 1400 includes a data section 1404, a department section 1406that identifies departments, and a filtered data section 1440.

As may be apparent, because of the full month time period, the number ofrecords in the data section 1404 and the filtered data section 1440 ismuch larger than illustrated in FIG. 12, but because the data is limitedto one facility, the number of records is smaller than illustrated inFIG. 13. Because of the additional data, the aggregation engine 902 isable to determine and display trending data in connection with each ofthe totals in the boxes in the filtered data section 1440. The trendingdata in all of the boxes represents trends at a facility level. Whenhovering over one of the boxes, the trending data may be presented in apopup window 1442. The trending data is a graph of the underlying dataassociated with the particular cell.

FIG. 15 is an example diagram illustrating a user interface 1500 thathas been customized with data aggregated from disparate sources,according to at least one example. The user interface 1500, which is anexample of the user interface 1400, is depicted in a web browser 1502 ona display device. The user interface 1500 in particular depicts data fora particular department over a full month. For example, a user may haveselected the “surgery” department from the list in the departmentsection 1406. The user interface 1500 includes a list of users 1546, ahome department list 1548, a shift list 1550, an activity event list1552, an exchange condition list 1554, and an indicator area 1556. Inthe indicator area 1556 is presented user interface elementscorresponding to a legend 1558. The user interface elements of the userinterface 1500 correspond to different computed values and derivedvalues from the one or more data sources such as the data stores912-918.

FIG. 16 is an example diagram illustrating a user interface 1600 thathas been customized with data aggregated from disparate sources,according to at least one example. The user interface 1600, which is anexample of the user interface 1500, is depicted in a web browser 1602 ona display device. The user interface 1600 in particular depicts data fora particular user over a full month. For example, a user may haveselected the “Jones, Mike” from the user list 1546 in the user interface1500.

The user interface 1600 includes various types of indicators, which canbe used to display patterns of the particular user. The types include,for example, a scheduled type 1660, a productive types 1662,non-productive type 1664, activity event types 1666, department type1668, unscheduled type 1670, and incremental types 1672. The userinterface 1600 also includes a legend 1658. The legend 1658 representsthe types of indicators that can be displayed in the table portion ofthe user interface 1600. The types of indicators have been describedwith references to other figures. These indicators are highlighted atthis time to point out that the same indicators can be used to monitorpatterns at many levels of granularity.

FIGS. 17 and 18 illustrate example flow diagrams showing respectiveprocesses 1700 and 1800, as described herein. These processes 1700 and1800 are illustrated as logical flow diagrams, each operation of whichrepresents a sequence of operations that can be implemented in hardware,computer instructions, or a combination thereof. In the context ofcomputer instructions, the operations represent computer-executableinstructions stored on one or more computer-readable storage media that,when executed by one or more processors, perform the recited operations.Generally, computer-executable instructions include routines, programs,objects, components, data structures, and the like that performparticular functions or implement particular data types. The order inwhich the operations are described is not intended to be construed as alimitation, and any number of the described operations can be omitted orcombined in any order and/or in parallel to implement the processes. Theorder in which the operations are described is not intended to beconstrued as a limitation, and any number of the described operationscan be omitted or combined in any order and/or in parallel to implementthe processes.

Additionally, some, any, or all of the processes may be performed underthe control of one or more computer systems configured with executableinstructions and may be implemented as code (e.g., executableinstructions, one or more computer programs, or one or moreapplications) executing collectively on one or more processors, byhardware, or combinations thereof. As noted above, the code may bestored on a computer-readable storage medium (e.g., storage devices),for example, in the form of a computer program comprising a plurality ofinstructions executable by one or more processors. The computer-readablestorage medium is non-transitory.

FIG. 17 is an example flowchart illustrating a process 1700 foraggregating data from disparate data sources for user interfacecustomization, according to at least one example. The process 1700 isperformed by the server system 902 including the aggregation engine 904,the rendering engine 910, and the notification engine 922. The process1700 in particular corresponds to a process by which users' activityevent records, reserved blocks, and exchange conditions are analyzed todetermine an overtime risk for the users.

The process 1700 begins at 1702 by the server system 902 retrievingfirst data corresponding to reserved blocks of a plurality of usersduring a predefined period. In some examples, the aggregation engine 904may perform block 1702. The first data may be retrieved from a firstdatabase (e.g., the reserved block data store 912) associated with afirst computer system. The predefined period may be user configurableand may be any suitable period such as a fixed number of hours, a day, aweek, a month, multiple months, a year, etc. In some examples, thereserved blocks may correspond to blocks of time.

At 1704, the process 1700 includes the server system 902 retrievingsecond data corresponding to a portion of the predefined period. In someexamples, the aggregation engine 904 may perform block 1704. The seconddata may be retrieved from a second database (e.g., the activity eventdata store 914) associated with a second computer system. The secondcomputer system may be operated and managed by a third-party such as atime management vendor. The second data includes a plurality of activityevents obtained from at least one capture device. For example, thesecond data may include punch data obtained from at least one timeclock. In some examples, only a portion of the predefined period isrelevant because while the first data may represent an entire period(e.g., a full weekly schedule), the second data may only representactual blocks that have been noted based on activity event data (e.g.,some portion of the full weekly schedule). In some examples, the firstcomputer system may be operated by a first entity and the secondcomputer system may be operated by a second entity that is distinct fromthe first entity.

At 1706, the process 1700 includes the server system 902 retrieving,third data defining exchange conditions. In some examples, theaggregation engine 904 may perform block 1706. The third data may beretrieved from a third database (e.g., exchange condition data store916).

At 1708, the process 1700 includes the server system 902 determiningfirst time for each of the plurality of users. In some examples, theaggregation engine 904 may perform block 1708. Determining the firsttime may be based at least in part on the first data from the firstdatabase, the second data from the second database, and the third datafrom the third database. In some examples, the first time may includeblocks of time during which the plurality of users were productive, orblocks that are otherwise characterized as productive.

At 1710, the process 1700 includes the server system 902 determiningsecond time for each of the plurality of users. In some examples, theaggregation engine 904 may perform block 1710. Determining the secondtime may be based at least in part on the first data from the firstdatabase. In some examples, the second time may include at least some ofthe reserved blocks. In particular, the second time may represent allscheduled time for the predefined time period.

At 1712, the process 1700 includes the server system 902 categorizingeach user of the plurality of users into one of a plurality ofcategories by at least performing sub-process 1712. The sub-process 1712includes at, 1714, the server system 902 determining a third time basedon the first time and the second time. The third time may be determinedfor each respective user. In some examples, the aggregation engine 904may perform block 1714. At 1716, the sub-process 1712 includes theserver system 902 filtering the third time with respect to a set oflevels (e.g., a set of thresholds). In some examples, the aggregationengine 904 may perform block 1716. At 1718, the sub-process 1712includes the server system 902 assigning each user to one of a pluralityof categories based at least in part on filtering the third time. Insome examples, the aggregation engine 904 may perform block 1718. Insome examples, the third time is a total expected time and includes acombination of the first time and the second time.

In some examples, a first level of the plurality of levels may be lessthan a first fixed value (e.g., 32), a second level of the plurality oflevels may be greater than or equal to the first fixed value (e.g., 32),and a third level of the plurality of levels may be greater than asecond fixed value (e.g., 40) that is greater than the first fixed value(e.g., 32).

At 1720, the process 1700 includes the server system 902 generating afirst user interface element corresponding to a first category of theplurality of categories. In some examples, the rendering engine 910 mayperform block 1720.

At 1722, the process 1700 includes the server system 902 providing auser interface for presentation at a user device that includes the firstuser interface element. In some examples, the rendering engine 910 mayperform block 1722. The user interface element may be displayed inassociation with each user categorized into the first category. In someexamples, other user interface elements are displayed in associationwith other users categorized into the second, third, and othercategories.

In some examples, the process 1700 further includes the server system902 generating, using the second data, a list including user identifiersand organizational unit identifiers. In this example, the useridentifiers may be associated with the plurality of users and theorganizational unit identifiers may be associated with organizationalunits at which the plurality of activity events occur. The process 1700may further include the server system using the list to identify asubset of users of the plurality of users that recorded activity eventsat a particular organizational unit that is outside of their homeorganizational unit, generating a notification that identifies thesubset of users, and providing the notification to a user deviceassociated with a user of the particular organizational unit. Theaggregation engine 904 may generate the list and identify the subset ofusers, and the notification engine 922 may generate the notification andprovide the notification to the user device.

FIG. 18 is an example flowchart illustrating a process for aggregatingdata from disparate data sources for user interface customization,according to at least one example. The process 1800 is performed by theserver system 902 including the aggregation engine 904, the renderingengine 910, and the notification engine 922. The process 1800 inparticular corresponds to a process by which users' activity eventrecords, reserved blocks, and exchange conditions are analyzed todetermine accrual of extra time.

The process 1800 begins at 1802 by the server system 902 retrievingfirst data corresponding to reserved blocks of a plurality of usersduring a predefined period. In some examples, the aggregation engine 904may perform the block 1802. The first data may be retrieved from a firstdatabase associated with a first computer system. Block 1802 may beperformed in a manner similar to the block 1702.

At 1804, the process 1800 includes the server system 902 retrievingsecond data corresponding to a portion of the predefined period. In someexamples, the aggregation engine 904 may perform block 1804. The seconddata may be retrieved from a second database associated with a secondcomputer system. The second data may include a plurality of activityevents obtained from at least one capture device (e.g., a punch clock).The block 1804 may be performed in a manner similar to the block 1704.

At 1806, the process 1800 includes the server system 902 retrievingthird data defining exchange conditions. In some examples, theaggregation engine 904 performs block 1806. The third data may beretrieved from a third database, which may be associated with the firstcomputer system, the second computer system, or a third computer system.The block 1806 may be performed in a manner similar to the block 1706.

At 1808, the process 1800 includes the server system 902 determiningthat a first user accrues first extra time by arriving before a firstreserved block. In some examples, the aggregation engine 904 performsblock 1808. The first user may be one of a plurality of users. The block1808 may be determined based on the first data from the first database,the second data from the second database, and the third data from thethird database.

At 1810, the process 1800 includes the server system 902 determiningthat the first user accrues second extra time by leaving after the firstreserved block. In some examples, the aggregation engine 904 performsblock 1810. The block 1810 may be determined based on the first datafrom the first database, the second data from the second database, andthe third data from the third database.

At 1812, the process 1800 includes the server system 902 generating afirst user interface element corresponding to the first extra time. Insome examples, the rendering engine 910 performs block 1812.

At 1814, the process 1800 includes the server system 902 generating asecond user interface element corresponding to the second extra time. Insome examples, the rendering engine 910 performs block 1814.

At 1816, the process 1800 includes the server system 902 providing auser interface for presentation at a user device, the user interfacecomprising the first user interface element and the second userinterface element. In some examples, the rendering engine 910 performsblock 1816. The user interface elements may be displayed in associationwith the first user.

In some examples, the process 1800 further includes the server system902 generating a notification that identifies the first user and atleast one of the first extra time or the second extra time, andtransmitting the notification to the user device. This may be performedby the notification engine 906.

In some examples, the user interface may include a timeline view thatincludes the first user interface element and the second user interfaceelement, along with a productive time user interface element.

Specific details are given in the above description to provide athorough understanding of the embodiments. However, it is understoodthat the embodiments may be practiced without these specific details.For example, circuits may be shown in block diagrams in order not toobscure the embodiments in unnecessary detail. In other instances,well-known circuits, processes, algorithms, structures, and techniquesmay be shown without unnecessary detail in order to avoid obscuring theembodiments.

Implementation of the techniques, blocks, steps and means describedabove may be done in various ways. For example, these techniques,blocks, steps and means may be implemented in hardware, software, or acombination thereof. For a hardware implementation, the processing unitsmay be implemented within one or more application specific integratedcircuits (ASICs), digital signal processors (DSPs), digital signalprocessing devices (DSPDs), programmable logic devices (PLDs), fieldprogrammable gate arrays (FPGAs), processors, controllers,micro-controllers, microprocessors, other electronic units designed toperform the functions described above, and/or a combination thereof.

Also, it is noted that the embodiments may be described as a processwhich is depicted as a flowchart, a flow diagram, a swim diagram, a dataflow diagram, a structure diagram, or a block diagram. Although adepiction may describe the operations as a sequential process, many ofthe operations can be performed in parallel or concurrently. Inaddition, the order of the operations may be re-arranged. A process isterminated when its operations are completed, but could have additionalsteps not included in the figure. A process may correspond to a method,a function, a procedure, a subroutine, a subprogram, etc. When a processcorresponds to a function, its termination corresponds to a return ofthe function to the calling function or the main function.

Furthermore, embodiments may be implemented by hardware, software,scripting languages, firmware, middleware, microcode, hardwaredescription languages, and/or any combination thereof. When implementedin software, firmware, middleware, scripting language, and/or microcode,the program code or code segments to perform the necessary tasks may bestored in a machine readable medium such as a storage medium. A codesegment or machine-executable instruction may represent a procedure, afunction, a subprogram, a program, a routine, a subroutine, a module, asoftware package, a script, a class, or any combination of instructions,data structures, and/or program statements. A code segment may becoupled to another code segment or a hardware circuit by passing and/orreceiving information, data, arguments, parameters, and/or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, etc.

For a firmware and/or software implementation, the methodologies may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. Any machine-readable mediumtangibly embodying instructions may be used in implementing themethodologies described herein. For example, software codes may bestored in a memory. Memory may be implemented within the processor orexternal to the processor. As used herein the term “memory” refers toany type of long term, short term, volatile, nonvolatile, or otherstorage medium and is not to be limited to any particular type of memoryor number of memories, or type of media upon which memory is stored.

Moreover, as disclosed herein, the term “storage medium” may representone or more memories for storing data, including read only memory (ROM),random access memory (RAM), magnetic RAM, core memory, magnetic diskstorage mediums, optical storage mediums, flash memory devices and/orother machine readable mediums for storing information. The term“machine-readable medium” includes, but is not limited to portable orfixed storage devices, optical storage devices, and/or various otherstorage mediums capable of storing that contain or carry instruction(s)and/or data.

While the principles of the disclosure have been described above inconnection with specific apparatuses and methods, it is to be clearlyunderstood that this description is made only by way of example and notas limitation on the scope of the disclosure.

What is claimed is:
 1. A computer-implemented method, comprising:retrieving, from a first database associated with a first computersystem, first data corresponding to reserved blocks of a plurality ofusers during a predefined period; retrieving, from a second databaseassociated with a second computer system, second data corresponding to aportion of the predefined period, the second data comprising a pluralityof activity actions obtained from at least one punch clock; retrieving,from a third database, third data defining exchange conditions;determining a number of times that each of the plurality of usersviolates an attendance policy of a plurality of attendance policiesbased at least in part on two or more of the first data from the firstdatabase, the second data from the second database, or the third datafrom the third database; identifying a subset of the plurality of usersfor whom a sum of the number of times exceeds a threshold; generatinguser interface elements corresponding to the subset of users of theplurality of users; and providing a user interface for presentation at auser device that includes the user interface elements displayed inassociation with each attendance policy of the plurality of attendancepolicies.
 2. The computer-implemented method of claim 1, wherein thefirst data comprises scheduling data that indicates times at which usersare scheduled for performing activities, wherein the second datacomprises punch clock data that is associated with the users, andwherein the third data comprises pay code data.
 3. Thecomputer-implemented method of claim 2, wherein the attendance policycomprises a policy that requires recordation of at least one of anarrival, a departure, or a break via a punch clock at a facility, andwherein determining the number of times that each of the plurality ofusers violates the attendance policy comprises comparing the schedulingdata for the respective user with the punch clock data for therespective user.
 4. The computer-implemented method of claim 2, whereinthe attendance policy comprises a policy that requires use of a punchclock within a particular department at a facility, and whereindetermining the number of times that each of the plurality of usersviolates the attendance policy comprises comparing the pay code data forthe respective user with the punch clock data for the respective user.5. The computer-implemented method of claim 2, wherein the attendancepolicy comprises a policy that requires use of a particular punch clockfor concluding a work period, and wherein determining the number oftimes that each of the plurality of users violates the attendance policycomprises comparing the pay code data for the respective user with thepunch clock data for the respective user.
 6. The computer-implementedmethod of claim 1, wherein the user interface elements identify at leastone a number of none punch outs, a number of early punch-outs, a numberof late punch-outs, a number of punch-outs in a different department, anumber of contractor punch-outs, a number of short breaks, a number oflong breaks, a total number of breaks, or a total number of meal breaks.7. The computer-implemented method of claim 1, further comprising:generating a trending user interface element that represents trendingdata associated with at least one attendance policy and at least oneuser interface element of the user interface elements; and updating theuser interface to include the trending user interface element forpresentation at the user device responsive to a user action with respectto the at least one user interface element.
 8. One or morenon-transitory computer-readable media comprising computer-executableinstructions that, when executed by one or more computer systems, causethe one or more computer systems to perform operations comprising:retrieving, from a first database associated with a first computersystem, first data corresponding to reserved blocks of a plurality ofusers during a predefined period; retrieving, from a second databaseassociated with a second computer system, second data corresponding to aportion of the predefined period, the second data comprising a pluralityof activity actions obtained from at least one punch clock; retrieving,from a third database, third data defining exchange conditions;determining a number of times that each of the plurality of usersviolates an attendance policy of a plurality of attendance policiesbased at least in part on two or more of the first data from the firstdatabase, the second data from the second database, or the third datafrom the third database; identifying a subset of the plurality of usersfor whom a sum of the number of times exceeds a threshold; generatinguser interface elements corresponding to the subset of users of theplurality of users; and providing a user interface for presentation at auser device that includes the user interface elements displayed inassociation with each attendance policy of the plurality of attendancepolicies.
 9. The one or more non-transitory computer-readable media ofclaim 8, wherein the first data comprises scheduling data that indicatestimes at which users are scheduled for performing activities, whereinthe second data comprises punch clock data that is associated with theusers, and wherein the third data comprises pay code data.
 10. The oneor more non-transitory computer-readable media of claim 9, wherein theattendance policy comprises a policy that requires recordation of atleast one of an arrival, a departure, or a break via a punch clock at afacility, and wherein determining the number of times that each of theplurality of users violates the attendance policy comprises comparingthe scheduling data for the respective user with the punch clock datafor the respective user.
 11. The one or more non-transitorycomputer-readable media of claim 9, wherein the attendance policycomprises a policy that requires use of a punch clock within aparticular department at a facility, and wherein determining the numberof times that each of the plurality of users violates the attendancepolicy comprises comparing the pay code data for the respective userwith the punch clock data for the respective user.
 12. The one or morenon-transitory computer-readable media of claim 9, wherein theattendance policy comprises a policy that requires use of a particularpunch clock for concluding a work period, and wherein determining thenumber of times that each of the plurality of users violates theattendance policy comprises comparing the pay code data for therespective user with the punch clock data for the respective user. 13.The one or more non-transitory computer-readable media of claim 8,wherein the user interface elements identify at least one a number ofnone punch outs, a number of early punch-outs, a number of latepunch-outs, a number of punch-outs in a different department, a numberof contractor punch-outs, a number of short breaks, a number of longbreaks, a total number of breaks, or a total number of meal breaks. 14.The one or more non-transitory computer-readable media of claim 8,wherein the one or more non-transitory computer-readable media comprisefurther instructions that, when executed, further cause the one or morecomputer systems to perform operations comprising: generating a trendinguser interface element that represents trending data associated with atleast one attendance policy and at least one user interface element ofthe user interface elements; and updating the user interface to includethe trending user interface element for presentation at the user deviceresponsive to a user action with respect to the at least one userinterface element.
 15. A system, comprising: a memory configured tostore computer-executable instructions; and a processor configured toaccess the memory and execute the computer-executable instructions to atleast: retrieve, from a first database associated with a first computersystem, first data corresponding to reserved blocks of a plurality ofusers during a predefined period; retrieve, from a second databaseassociated with a second computer system, second data corresponding to aportion of the predefined period, the second data comprising a pluralityof activity actions obtained from at least one punch clock; retrieve,from a third database, third data defining exchange conditions;determine a number of times that each of the plurality of users violatesan attendance policy of a plurality of attendance policies based atleast in part on two or more of the first data from the first database,the second data from the second database, or the third data from thethird database; identify a subset of the plurality of users for whom asum of the number of times exceeds a threshold; generate user interfaceelements corresponding to the subset of users of the plurality of users;and provide a user interface for presentation at a user device thatincludes the user interface elements displayed in association with eachattendance policy of the plurality of attendance policies.
 16. Thesystem of claim 15, wherein the first data comprises scheduling datathat indicates times at which users are scheduled for performingactivities, wherein the second data comprises punch clock data that isassociated with the users, and wherein the third data comprises pay codedata.
 17. The system of claim 16, wherein the attendance policycomprises a policy that requires recordation of at least one of anarrival, a departure, or a break via a punch clock at a facility, andwherein determining the number of times that each of the plurality ofusers violates the attendance policy comprises comparing the schedulingdata for the respective user with the punch clock data for therespective user.
 18. The system of claim 16, wherein the attendancepolicy comprises a policy that requires use of a punch clock within aparticular department at a facility, and wherein determining the numberof times that each of the plurality of users violates the attendancepolicy comprises comparing the pay code data for the respective userwith the punch clock data for the respective user.
 19. The system ofclaim 16, wherein the attendance policy comprises a policy that requiresuse of a particular punch clock for concluding a work period, andwherein determining the number of times that each of the plurality ofusers violates the attendance policy comprises comparing the pay codedata for the respective user with the punch clock data for therespective user.
 20. The system of claim 15, wherein the memorycomprises further computer-executable instructions, and the processor isconfigured to access the memory and execute the furthercomputer-executable instructions to: generate a trending user interfaceelement that represents trending data associated with at least oneattendance policy and at least one of the user interface elements; andupdate the user interface to include the trending user interface elementfor presentation at the user device responsive to a user action withrespect to the at least one user interface element.